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Scientist, writer, policy advocate, YouTuber – before Jordan Harrod established her many successful career identities, her first role was as a student athlete. While she enjoyed competing in everything from figure skating to fencing, she also sustained injuries that left her with chronic pain. These experiences as a patient laid the groundwork for an interest in biomedical research and engineering. “I knew I wanted to make tools that would help people with health issues similar to myself,” she says.
Harrod went on to pursue her BS in biomedical engineering at Cornell University. Before graduating, she spent a summer at Stanford University doing machine-learning research for MRI reconstruction. “I didn’t know anything about machine learning before that, so I did a lot of learning on the fly,” she says. “I realized that I enjoyed playing with data in different ways. Machine learning was also becoming the new big thing at the time, so it felt like an exciting path to follow.”
Harrod looked for PhD programs that would combine her interests in helping patients, biomedical engineering, and machine learning. She came across the Harvard-MIT Program in Health Sciences and Technology (HST) and realized it would be the perfect fit. The interdisciplinary program requires students to perform clinical rotations and take introductory courses alongside medical students. “I’ve found that the clinical perspective was often underrated on the research side, so I wanted to make sure I’d have that. My goal was that my research would be translatable to the real world,” Harrod says.
Mapping the brain to understand consciousness
Today, Harrod collaborates with professors Emery Brown, an anesthesiologist, and Ed Boyden, a neuroscientist, to study how different parts of the brain relate to consciousness and arousal. They seek to understand how the brain operates under different states of consciousness and the way this affects the processing of signals associated with pain. By studying arousal in mice and applying statistical tools to analyze large datasets of activated brain regions, for example, Brown’s team hopes to improve the current understanding of anesthesia.
“This is another step toward creating better anesthesia regimens for individual patients,” says Harrod.
Since beginning her neuroscience research, Harrod has been amazed to learn how much about the brain still needs to be uncovered. In addition to understanding biological mechanisms, she believes there is still work to be done at a preliminary cause and effect level. “We’re still learning how different arousal centers work together to modulate consciousness, or what happens if you turn one off,” says Harrod. “I don’t think I realized the magnitude or the difficulty of the challenge, let alone how hard it is to translate our research to brains in people.”
“I didn’t come into graduate school with a neuroscience background, so every day is an opportunity to learn new things about the brain. Even after three years, I’m still amazed with how much we have yet to discover.”
Sharing knowledge online and beyond
Outside of the lab, Harrod focuses her time on communicating research to the public and advocating for improved science policies. She is the chair of the External Affairs Board of the Graduate Student Council, an Early Career Policy Ambassador for the Society for Neuroscience, and the co-founder of the MIT Science Policy Review, which publishes peer reviewed reports on different science policy issues.
“Most of our research is funded by our taxpayers, yet most people don’t necessarily understand what’s going on in the research that they’re funding,” explains Harrod. “I wanted to create a way so people could better understand how different regulations affect them personally.”
In addition to her advocacy roles, Harrod also has a dedicated online presence. She writes articles for Massive Science and is well-known for her YouTube channel. Her videos, released weekly, investigate the different ways we interact with artificial intelligence daily. What began as a hobby three years ago has developed into an active community with 70,000 subscribers. “I hadn’t seen many other people talking about AI and machine learning in a casual way, so I decided to do it for fun,” she says. “It’s been a great way to keep me looped into the broader field questions.”
Harrod’s most popular video focuses on how AI can be used to monitor online exam proctoring. With the shift to online learning occurring during the pandemic, many students have used her video to understand how AI proctors can detect cheating. “As the audience grows, it’s been exciting to read the comments and see people get curious about AI applications they had never heard of before. I’ve also gotten to have interesting conversations with people who I wouldn’t have come across otherwise,” she says.
In the future, Harrod hopes to find a career that will allow her to balance her time between lab research, policy, and science communication. She plans on continuing to use her knowledge as a scientist to debunk hype and tell truthful stories to the public. “I’ve seen so many articles with headlines that could be misleading if someone only read the title. For example, a small study done in mice can be exaggerated to make mind-reading technology seem real, when the research still has a long way to go.”
“Since making my YouTube channel, I’ve learned it’s important to give people reasonable expectations about what’s real and what they’re going to encounter in their lives. They deserve to know the full picture so they can make informed decisions,” she says.
MIT PhD students Aziza Almanakly and Belinda Li have been selected as the Department of Electrical Engineering and Computer Science (EECS) recipients of the multi-year Clare Boothe Luce Graduate Fellowship for Women, an honor designed to encourage and support graduate women in STEM. The rigorous selection process for this prestigious fellowship took into account the two students’ outstanding track record of scientific achievement and inquiry, as well as their contributions to the STEM community.
Importantly, the fellowships represent the culmination of an intensive effort on the part of both the Institute and the EECS department. Upon MIT's selection by the Clare Boothe Luce Program for Women in STEM to submit a full proposal, EECS entered the MIT internal competition and was selected to submit a full application on behalf of the Institute to the national competition held by the Henry Luce Foundation. Funds from the Luce Foundation, combined with cost-sharing funds from EECS, will provide full financial support for a period of two years for Almanakly and Li.
“These fellowships are a powerful assertion of institutional support for women in STEM,” says Professor Asu Ozdaglar, head of EECS. “Our dedication to supporting women in STEM extends far beyond attracting top candidates to our program; we are committed to providing continued, concrete support to their research careers once they arrive at MIT.” Both Almanakly and Li will be deferring the start of their CBL Graduate Fellowships until they complete their current fellowship awards; the two recipients are already capturing attention in the red-hot technical fields of quantum computing and language modeling.
A rising second-year PhD candidate advised by Professor Will Oliver, Aziza Almanakly conducts research on waveguide quantum electrodynamics and microwave quantum optics with superconducting qubits. Within the first nine months of her time at MIT, Almanakly successfully demonstrated controlled, directional generation of single microwave photons on a new qubit chip of her own design — a novel accomplishment, and an indicator of her exceptional talent. Of Almanakly’s work, Oliver says, “Her success is rooted in a combination of raw talent, strong intuition, perseverance, and a strong desire to improve herself, her research, her workplace, and the lives of those around her. I have absolutely no doubt that Aziza will succeed in her research, and I fully expect she will become a future leader in science and technology.” As part of her personal commitment to passing on the mentorship and encouragement she has received, Almanakly teaches the fundamentals of quantum computing to underrepresented high school students through IBM Quantum and the Coding School. Prior to her arrival at MIT, Almanakly conducted research at New York University, Caltech, the City University of New York, and Princeton University. Among other honors, Almanakly has won the P.D. Soros Fellowship for New Americans.
A rising second-year PhD candidate advised by Professor Jacob Andreas, Belinda Li conducts research on language models and natural language processing. Li’s interest in language models and natural language processing was fueled by a year spent working with the AI Integrity team within the Facebook AI Applied Research group, in which she worked on building automated detectors for hate speech and misinformation. Of her work, Li says, “I am interested in interrogating the relationship between language models (LMs) and the knowledge they encode: what exactly do LMs know about the external world? And how can we expand their ability to learn and utilize such knowledge in a systematic way? More fundamentally, what is the relationship between language/language technologies, and the broader society?” Li’s ambitious research goals have taken her far within her first year at MIT. Her advisor Andreas reports: “Despite starting this year [during the pandemic], Belinda has already made significant discoveries about the organization of information in machine learning models trained for language processing tasks … In the six months she’s been here, Belinda has basically started running a mini-lab of her own.” Additionally, Li has taken on the responsibility of mentoring underrepresented undergrads through MIT EECS’s GAAP program. Among many other awards, Li has been named a recipient of the Ida M. Green Memorial Fellowship, the National Science Foundation Graduate Research Fellowship, and the National Defense Science and Engineering Graduate Fellowship.
Established by the prominent American journalist, playwright, ambassador, and Congresswoman Clare Boothe Luce, the CBL Program for Women in STEM was created “to encourage women to enter, study, graduate, and teach” in areas in which they continue to be underrepresented, including science, mathematics, and engineering. To date, the program has supported more than 2,800 women at the undergraduate, graduate, and beginning tenure-track faculty stages, making the CBL program the single most significant source of private support for women in science, mathematics, and engineering in higher education in the United States.
“I took this picture from the opposite side of the Charles River in a clear Friday evening. I used a tripod and a 70-300mm telescope lens with long time exposure to capture the amazing glow of the sunset and the reflection on the river. It’s lucky that I can seize this moment of our campus, since I’ve noticed that the surface of the river is ever changing every day. When it is cloudy or windy, it’s relatively hard to get a tranquil and clear surface for the beautiful reflections of sunset and lights from the Great Dome.
I am a postdoc in experimental condensed-matter physics. Currently I am studying the fascinating electrical and optical properties of two-dimensional quantum materials, such as graphene. Having been here at MIT for over two years, I am always enjoying the challenges in research and also the life on campus.
I love taking pictures during my leisure time. I feel that the moment I press the shutter is like freezing a slice of time from the flow. Scenes along the Charles River are among my favorites. I love the sense of seasons changing when I observe the river freezing, the trees blossoming, the full moon rising, etc. To me, the days doing research at MIT and the pictures taken here are an invaluable treasure of my life.”
—Tianyi Han, postdoc in the Department of Physics
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It’s a cloudy July afternoon in Cambridge, Massachusetts, and MIT Edgerton Center Instructor Amanda Mayer is using brightly-colored plastic to build proteins. She takes a small yellow block and moves it to the end of a chain of blue and green ones, clicking it into place. “Congratulations,” she says to the four high school students guiding her hand over Zoom. “You’ve all become synthetic biologists.”
Together, the group has assembled a model of the complex molecules found in their food and bodies. “I used to think proteins were just one thing,” says a high school student named Fatima, who has the same blocks laid out before her at home. “Now I know that what I ate has lots and lots of amino acids in it.”
Mayer is one of two biologists who are crafting models and lesson plans that schoolteachers around the country — and the world — are using to teach their students about one of the most fundamental concepts in biology: how cells use DNA to make proteins. Both she and Kathy Vandiver, MIT Edgerton Center advisor and director of the Community Outreach Education and Engagement Core at the MIT Center for Environmental Health Sciences, discovered their love for sharing biology with schoolchildren after completing their PhDs.
Vandiver, who spent 16 years teaching middle school science before joining MIT in 2005, created classroom models throughout her career. In 2008, Mayer joined her at the Edgerton Center, helping her perfect the lessons and activity booklets that accompany the models. The duo uses their sets to teach students and schoolteachers, as well as nurses and biotechnologists. “This is about helping other people learn more about biology, and making it much more accessible,” Vandiver says.
Creating life: From blueprints to building blocks
In school, students learn that DNA determines the features they inherit from their parents, like the color of their eyes. This is because DNA contains the instructions for making proteins, which in turn make up our cells. Vandiver says that even though protein synthesis is the one lesson that every biology teacher has to teach, proteins don’t always get the attention they deserve. “DNA is the glamour molecule — it’s on T-shirts everywhere,” she says. “But DNA just stores the instructions for building proteins. They do all the work in the cell.”
Vandiver believes that if students are to grasp tricky processes like protein synthesis, they need more than just the labeled diagrams found frequently in science classrooms. Tactile decision-making is a much more engaging method of learning than looking at a diagram, or even watching a video, she says. “When you watch a cell do different things, you can still tune out. But here, you have to make a decision.”
Since students can learn by doing, they’re also not held back by the pressure to master vocabulary, a typical hurdle in the biology classroom. The models are useful for various levels: a sixth grader may use them simply as building blocks, while older students can use clever design details to learn higher-level concepts, such as directionality and bond strength.
Vandiver and Mayer are careful to put as much thought into the lessons that accompany the models. For a protein to do its job, its building blocks must be strung together in the right sequence. The standard classroom strategy for teaching protein synthesis is a chronological one, Vandiver says, in which the information stored in DNA is first transferred to another molecule called RNA, and then finally to proteins.
“But it’s so confusing for the students. They’re going through this multitude of steps, and they have no idea what they’re making,” she explains. Over the years, as Vandiver and Mayer taught thousands of students of different ages at the MIT Museum, they observed that students learned protein synthesis much better if they already knew what the end product looked like. So, in their lessons, students begin with a finished protein, containing a specific sequence of amino acids. Then they start from scratch, learning and following the body’s steps for putting those pieces together.
Working with teachers
Throughout the year, Mayer and Vandiver hold workshops for teachers in Massachusetts, Texas, and Arizona, training them how to use the kits. With the help of a grant, they’ve distributed sets to 30 of Boston’s public high schools for teachers to use in their classrooms.
Mayer says that after working with the kits, teachers understand the material much better — and feel more confident about teaching it. “Teaching teachers is fantastic,” she says. “Think of all the students they’ll teach in their lifetimes, and how many biologists they’re going to create by making students excited about doing this.”
The DNA kits are being used in other countries, as well: Vandiver has trained teachers in Italy, India, China, Singapore, Cambodia, and Mexico. And when the center occasionally hosts students from abroad, Mayer and Vandiver hold workshops for them.
They also work with local students. For the past five summers, MIT’s biology department has partnered with the LEAH Knox Scholars program to host talented high-school students from communities underrepresented in science. Every year, the Edgerton Center kicks the program off by offering the students a crash course in molecular biology. “With the DNA kits, I actually felt like I was inside the cell in some way,” says Breetika Maharjan, a high-school senior who attended one of the workshops. “It wasn’t like a boring high-school textbook with just words.”
Mayer and Vandiver say they’ve still got a lot to do. Since 2014, they’ve been importing the parts for their kits from Singapore and assembling them in Cambridge with the help of volunteers; this allows them to offer the kits to educators at cost. They have a new set on chromosomes on the way, and they’re constantly designing lessons for new audiences such as nurses, who may soon be caring for patients with DNA-tailored treatment plans.
“The number one comment we get from people after they go through our lessons and play with this is, ‘Oh wow, if I had this, I would probably have liked biology. I might even have become a biology researcher,’” says Mayer.
Vandiver believes the kits are successful because they embody Doc Edgerton’s memorable motto about teaching: “The trick to education,” she quotes, “is to not let them know they’re learning anything until it’s too late.”
Patricia Pujols grew up in the city of Ponce, Puerto Rico, fascinated by documentaries she had seen about human behavior and psychology. She wanted to learn the molecular roots of things like memory, love, hate, happiness, and anger. Despite her early curiosity, becoming a scientist and studying these phenomena didn’t seem like a possibility.
“Where I grew up, people didn't really encourage me to study science,” she says. Instead, she initially pursued a career in accounting. “Later on, after the death of my father, I realized life is short. I prefer to do the thing that I love and am passionate about. And for me, that is teaching and learning science.”
With a strong network of mentors to inspire and push her, Pujols is now well on her way to becoming a scientist. She has a semester left in her undergraduate degree at Universidad Central de Bayamón in Puerto Rico, where she is pursuing a major in neuroscience and a minor in psychology. After she graduates, she plans to earn a PhD. This summer, she was part of the MIT Summer Research Program in Biology (MSRP-Bio), which invites non-MIT undergraduate science majors to the Institute for 10 weeks of summer research.
“MSRP-Bio is designed for students like Patricia, who are driven and passionate about science, with limited access to research at their own institution and ready for a challenging and rigorous research experience at MIT that will prepare them for graduate school and open a lot of doors,” says Mandana Sassanfar, the Department of Biology’s director of outreach. “In addition, the program greatly facilitates access to MIT faculty and graduate students and provides a strong community-building component to give students a sense of belonging.”
Pujols arrived at MIT through the guidance of one of her undergraduate professors, molecular neuroscientist Ramon Jorquera. Jorquera worked with Pujols back in Puerto Rico, and is now at the Universidad Andrés Bello in Santiago, Chile.
“He was the first person to invite me to a research lab,” Pujols says. “He has helped me a lot with everything, with gaining confidence, with my English language skills, and with seeing that I can really do this.”
Years ago, Jorquera worked as a fellow in the lab of Troy Littleton, the Menicon Professor of Biology at MIT and the Picower Institute for Learning and Memory. It was Jorquera who encouraged Pujols to apply to a research program at the University of North Carolina at Charlotte several summers ago, and then to apply to MSRP-Bio. Now, just like her mentor, Pujols is working in the Littleton lab to answer crucial questions about human behavior.
Every summer, the Littleton lab welcomes MSRP students.
“This year, while pairing candidates, Patricia was sort of an obvious match for us in terms of her prior research and interests,” Littleton says. “The major interest of my lab is to really understand how neurons talk to each other within the nervous system. The ability of neurons to rapidly communicate drives our behavior, ability to learn, and to remember. That biology all occurs at specific sites known as synapses, where neurons connect with each other.”
Problems in synapse formation or function contribute to the progression of brain disorders and diseases including Alzheimer’s, Parkinson’s, schizophrenia, and many others.
At each of the billions of synapses in the human nervous system, one neuron sends a chemical message and the next receives it –– just like two friends texting. The sender is known as the presynaptic neuron, and the receiver is called the postsynaptic neuron. To allow for seamless, rapid transit of information, the sites where the chemicals are released from on the presynaptic neuron must perfectly align with the receptors on the postsynaptic neuron.
“All of our work is built around genetics,” Littleton says. “We do manipulations where you take out a gene or alter its coding a bit and see how things change. This allows us to piece together how the individual proteins at synapses work to allow neurons to effectively talk to each other.”
To conduct their work, the Littleton lab uses Drosophila melanogaster, the common fruit fly whose genome is well-characterized and is widely used as a genetic model system. After removing a piece of genetic code, they can image the fly’s synapses to see if there was a change in the alignment of the synaptic chemical receptors. They also test if the synapses’ ability to actually transmit and receive chemical messages has changed.
This summer, Pujols is studying the neuromuscular junction, a particular type of synapse where a motor neuron communicates with a muscle cell. This communication enables movement.
In mammals, the motor neuron (the sender, in this case), secretes a protein called agrin that helps to align the key components of the synapse. Agrin is important for organizing acetylcholine receptors in the synapse. Acetylcholine is a neurotransmitter released from motor neurons that is essential for movement. Mutations in agrin in humans can therefore cause muscular dystrophies and various autoimmune disorders.
In Drosophila, it is a neurotransmitter called glutamate, not acetylcholine, that operates at the neuromuscular junction. Researchers want to know if the way that agrin organizes acetylcholine receptors in the mammalian neuromuscular junction is similar to the way that a protein called perlecan organizes the neuromuscular junctions in Drosophila.
To address this question, Pujols has spent her summer removing perlecan from either the sending motor neuron or the receiving muscle cell in Drosophila, and examining how synapse formation and clustering of glutamate receptors is altered. Pujols is working closely with PhD candidate Ellen Guss in a partnership she calls “the best experience ever.”
Both Littleton and Pujols stress the importance of mentorship in the journey to becoming a scientist. When he was an undergraduate at Louisiana State University, Littleton spent a summer at the University of Florida, working with a scientist whose guidance shaped him. That summer was one of his most influential experiences as a scientist, he says.
At MIT, Pujols says, “I stepped out of my comfort zone and strengthened my skills. MSRP gave me all the tools I needed to have an enriching experience in science, as well as the opportunity to meet colleagues that I will remember for the rest of my life.”
To other students thinking of pursuing a career as a scientist, Pujols says, “don’t be afraid.”
“You will get a lot of opinions about what to do, that it’s too difficult, or you don't have the potential, or some other negative thing,” Pujols says. “I think the most important thing is that you do what you love, even though maybe you are going against the current. You don’t want to have regrets.”
On glowing screens in 41 countries across the world, over 680 people logged on to the second TESS Science Conference from Aug. 2-6. Experts not only in exoplanets, but also in extragalactic astronomy, stellar astrophysics, data analysis, and solar system science presented on discoveries made possible by the NASA TESS Mission via 193 posters uploaded to Zenodo and 50 talks livestreamed and archived on YouTube, with views numbering in the thousands. The conference, hosted by the MIT Kavli Institute for Astrophysics and Space Research, also boasted a vibrant community of online participants across Slack, gather.town, and the conference hashtag, #TESScon2. Attendees shared photos of pets, screenshots of avatars congregated in the virtual conference hall, and reactions to the new NASA TESS poster released during the conference.
This TESS Science Conference took place two years following the first conference, held at MIT in 2019, and three years after TESS began its full-sky survey to find thousands of exoplanets orbiting bright nearby stars. As mission principal investigator, MIT Senior Research Scientist George Ricker stated in his opening remarks that since the four TESS cameras started imaging the sky in summer 2018, TESS has discovered thousands of exoplanet candidates. The mission has surpassed its primary science requirement of confirming 50 new planets smaller than Neptune (or smaller than four times Earth’s radius) and measuring their masses. This success is due in large part to the open-ended and abundant nature of the TESS data.
In two 13.7-day orbits per observing period, TESS takes a continuous series of "postage stamp"-sized images of 20,000 preselected stars every two minutes. It also records wide-field images of a 24-by-96-degree swath of the sky (approximately four times the sky area of the constellation Orion, or close to 6 percent of the entire sky) taken in ever-shrinking frequency intervals: first every 30 minutes for the two years of the TESS prime mission (August 2018-June 2020), then every 10 minutes during the first TESS extended mission (July 2020-April 2022), and now potentially every 200 seconds in the proposed second TESS extended mission, which would start in early fall 2022. Astronomers are resorting to machine learning and heavy-duty computing resources to handle the ever-growing body of TESS data.
Astronomers have found a near-endless variety of uses for TESS's month-long "stop-motion movies" of millions of stars. The diversity of topics presented at the TESS Science Conference, from within the Solar System to beyond the galaxy attests to how versatile the TESS data are. Beyond exoplanets and stellar astrophysics, the mainstays of the first TESS conference, this year's meeting included asteroseismology, cosmic geochronology, asteroids, the search for Planet 9, and even SETI. All TESS data are publicly available, with a wide variety of open-access platforms and software packages for data analysis. In addition to the hundreds of professional astronomers who are diving into the TESS data, over 30,000 citizen-scientists have contributed to the discovery and follow-up of new TESS exoplanet candidates and supernovae.
Looking ahead, TESS will continue to work in concert with other missions, providing promising exoplanets for more in-depth study, and contributing visible light observations of supernovae and active galactic nuclei observed also by other telescopes in other wavelengths. TESS has already entered the realm of big-data astronomy, and will likely continue the trend based on plans for future extended missions with full-frame images every 200 seconds, more frequent data downlinks from TESS to Earth, and the possibility of another TESS-like spacecraft in orbit.
At the conference's conclusion, Ricker remarked, "TESS is everything that we had dreamed that it might be … certainly it was my dream come true, in that sense." With TESS Science Conference III on the horizon in 2024, Ricker and the collaborative TESS community fully expect to continue making new and unexpected discoveries with this unique space telescope.
TESS is a NASA Astrophysics Explorer mission led and operated by MIT in Cambridge, Massachusetts, and managed by NASA's Goddard Space Flight Center. Additional partners include Northrop Grumman, based in Falls Church, Virginia; NASA’s Ames Research Center in California’s Silicon Valley; the Center for Astrophysics | Harvard & Smithsonian in Cambridge, Massachusetts; MIT’s Lincoln Laboratory; and the Space Telescope Science Institute in Baltimore, Maryland. More than a dozen universities, research institutes, and observatories worldwide are participants in the mission.
It’s rare for a pre-teen to become enamored with thermodynamics, but those consumed by such a passion may consider themselves lucky to end up at a place like MIT. Madhumitha Ravichandran certainly does. A PhD student in Nuclear Science and Engineering (NSE), Ravichandran first encountered the laws of thermodynamics as a middle school student in Chennai, India. “They made complete sense to me,” she says. “While looking at the refrigerator at home, I wondered if I might someday build energy systems that utilized these same principles. That’s how it started, and I’ve sustained that interest ever since.”
She’s now drawing on her knowledge of thermodynamics in research carried out in the laboratory of NSE Assistant Professor Matteo Bucci, her doctoral supervisor. Ravichandran and Bucci are gaining key insights into the “boiling crisis” — a problem that has long saddled the energy industry.
Ravichandran was well prepared for this work by the time she arrived at MIT in 2017. As an undergraduate at India’s Sastra University, she pursued research on “two-phase flows,” examining the transitions water undergoes between its liquid and gaseous forms. She continued to study droplet evaporation and related phenomena during an internship in early 2017 in the Bucci Lab. That was an eye-opening experience, Ravichandran explains. “Back at my university in India, only 2 to 3 percent of the mechanical engineering students were women, and there were no women on the faculty. It was the first time I had faced social inequities because of my gender, and I went through some struggles, to say the least.”
MIT offered a welcome contrast. “The amount of freedom I was given made me extremely happy,” she says. “I was always encouraged to explore my ideas, and I always felt included.” She was doubly happy because, midway through the internship, she learned that she’d been accepted to MIT’s graduate program.
As a PhD student, her research has followed a similar path. She continues to study boiling and heat transfer, but Bucci gave this work some added urgency. They’re now investigating the aforementioned boiling crisis, which affects nuclear reactors and other kinds of power plants that rely on steam generation to drive turbines. In a light water nuclear reactor, water is heated by fuel rods in which nuclear fission has occurred. Heat removal is most efficient when the water circulating past the rods boils. However, if too many bubbles form on the surface, enveloping the fuel rods in a layer of vapor, heat transfer is greatly reduced. That’s not only diminishes power generation, it can also be dangerous because the fuel rods must be continuously cooled to avoid a dreaded meltdown accident.
Nuclear plants operate at low power ratings to provide an ample safety margin and thereby prevent such a scenario from occurring. Ravichandran believes these standards may be overly cautious, owing to the fact that people aren’t yet sure of the conditions that bring about the boiling crisis. This hurts the economic viability of nuclear power, she says, at a time when we desperately need carbon-free power sources. But Ravichandran and other researchers in the Bucci Lab are starting to fill some major gaps in our understanding.
They initially ran experiments to determine how quickly bubbles form when water hits a hot surface, how big the bubbles get, how long they grow, and how the surface temperature changes. “A typical experiment lasted two minutes, but it took more than three weeks to pick out every bubble that formed and track its growth and evolution,” Ravichandran explains.
To streamline this process, she and Bucci are implementing a machine learning approach, based on neural network technology. Neural networks are good at recognizing patterns, including those associated with bubble nucleation. “These networks are data hungry,” Ravichandran says. “The more data they’re fed, the better they perform.” The networks were trained on experimental results pertaining to bubble formation on different surfaces; the networks were then tested on surfaces for which the NSE researchers had no data and didn’t know what to expect.
After gaining experimental validation of the output from the machine learning models, the team is now trying to get these models to make reliable predictions as to when the bubble crisis, itself, will occur. The ultimate goal is to have a fully autonomous system that can not only predict the boiling crisis, but also show why it happens and automatically shut down experiments before things go too far and lab equipment starts melting.
In the meantime, Ravichandran and Bucci have made some important theoretical advances, which they report on in a recently published paper for Applied Physics Letters. There had been a debate in the nuclear engineering community as to whether the boiling crisis is caused by bubbles covering the fuel rod surface or due to bubbles growing on top of each other, extending outward from the surface. Ravichandran and Bucci determined that it is a surface-level phenomenon. In addition, they’ve identified the three main factors that trigger the boiling crisis. First, there’s the number of bubbles that form over a given surface area and, second, the average bubble size. The third factor is the product of the bubble frequency (the number of bubbles forming within a second at a given site) and the time it takes for a bubble to reach its full size.
Ravichandran is happy to have shed some new light on this issue but acknowledges that there’s still much work to be done. Although her research agenda is ambitious and nearly all consuming, she never forgets where she came from and the sense of isolation she felt while studying engineering as an undergraduate. She has, on her own initiative, been mentoring female engineering students in India, providing both research guidance and career advice.
“I sometimes feel there was a reason I went through those early hardships,” Ravichandran says. “That’s what made me decide that I want to be an educator.” She’s also grateful for the opportunities that have opened up for her since coming to MIT. A recipient of a 2021-22 MathWorks Engineering Fellowship, she says, “now it feels like the only limits on me are those that I’ve placed on myself.”
In 2010, the city of Rio de Janeiro opened its Operations Center, a high-tech command post centralizing the activities of 30 agencies. With its banks of monitors looming over rows of employees, the center brings flows of information to city leaders regarding crime, traffic, and emergency preparedness, among other things, to help officials anticipate and solve problems.
That’s one vision of technology and urban life. Another, quite different vision of deploying technology debuted in Rio six years later, at architect Guto Requena’s Dancing Pavilion, built for the 2016 summer Olympics. The pavilion had a dance floor, banks of mirrors rotating in response to people’s movement, and lighting that changed according to the activity levels in the building. The goal was to enhance sociality and spontaneity.
Between these two alternate applications of large-scale technology in public places, MIT urban studies researchers Fabio Duarte and Ricardo Alvarez have a clear favorite: the Dancing Pavilion, and its ever-evolving interplay of people and the built environment, as opposed to the deployment of technology as a tracking tool monitoring urban systems.
“There is this notion of an optimal city where everything works perfectly well, where everything can be not only planned but also predicted,” Duarte says. “But in reality you cannot predict everything that happens. We should not remove from urban life the serendipity, all the things that happen by chance. Surprise is important for urban life.”
Now Duarte and Alvarez, researchers in MIT’s School of Architecture and Planning, have written a book making the case for using high-tech tools to enhance playfulness and creativity in urban environments. The book, “Urban Play: Make-Believe, Technology, and Space,” is being published this month by the MIT Press.
“The argument of the book is, we can use technology to bring back serendipity and fantasy in the design of cities,” says Duarte, a lecturer in MIT’s Department of Urban Studies and Planning, and a principal research scientist at MIT’s Senseable Cities Lab. “We are not putting technology aside. We can sustain the openness of urban life through technology.”
In the book, Duarte and Alvarez discuss multiple ways technology can make cities more playful places. Some cities, they observe, have play as a main rationale and express this through creative large-scale design — think Las Vegas, Orlando, or even Dubai, places designed around leisure.
“Nobody moves to a city because it has the optimal public transportation system,” says Alvarez, who is a postdoc at the Senseable City Lab. “So [the question] is, how do you use technology to create spaces that resonate emotionally? Because that’s where people want to live, that’s where people want to go.”
Both Disneyland and Disney World, as Duarte and Alvarez detail in the book, embraced experimentalism in design and a belief that technology could create new urban forms — think of the Disney monorails, Tomorrowland, or Epcot.
“Walt Disney was deeply into city-making and tried to present future ways of living,” Alvarez says. “The original EPCOT Center wasn’t going to be a theme park. It was going to be a prototype city. At some point he saw very clearly that his vision, whether we like it or not, was resonating with people. Some architects may call it artifice or kitsch, but the fact of the matter is, people flock to these places. They use technology for purposes of pleasure and fun and storytelling.”
In another vein, the authors suggest that video games have much to offer in urban design, as the industry has developed increasingly sophisticated urban simulations across dozens of games in recent decades.
“The video game industry is similar to architecture and urban planning, in that they both create interactive spaces,” Alvarez observes. “Through time, [game developers] have learned a lot from architecture and planning. But in the virtual world they also have a lot more freedom to experiment, to take concepts and explore them to their ultimate form.”
Moreover, Alvarez notes, “What the gaming industry does is bring people and testers a lot earlier in the design stage. You get feedback from people and inject that into the design process. This is a very common process in the video game world that the planning and architecture fields could benefit from.”
The authors also suggest that virtual reality could emerge as a more robust design tool than people realize, by offering alternate perspectives to designers. A child, as they note in the book, views a playground in a park from a different than an adult does; virtual reality might similarly help some designers see space in new ways.
“Virtual reality is powerful for its perspective,” Duarte says. “Once you see this type of representation, you can start playing with the world in this way. When I can change completely how I perceive the world through this technology, how can I design the world differently?”
Duarte and Alvarez believe their ideas have received a fair hearing from urbanists and designers as they have been working on the book, and hope it will be read by people with an array of interests. Richard Florida, a university professor at the University of Toronto, has called the new work “a guidebook for getting us and our cities out of our regimented rut and a manifesto for building better cities and a better way of life.”
For their part, Duarte and Alvarez acknowledge that new technology is necessary to make urban infrastructure and system work well. But they hope it is viewed as a means of not only achieving efficiency but realizing urban vitality.
“Let’s try to use technology, not to try to predict the future, or create an optimized reality, but to explore different possibilities of living,” Duarte says. “I think we now have the chance to create new possibilities all the time.”
As students, faculty, and staff prepare for a full return to the MIT campus in the weeks ahead, procedures for entering buildings, navigating classrooms and labs, and interacting with friends and colleagues will likely take some getting used to.
The Institute recently reinforced its policies for indoor masking and has also continued to require regular testing for people who live, work, or study on campus — procedures that apply to both vaccinated and unvaccinated individuals. Vaccination is required for all students, faculty, and staff on campus unless a medical or religious exemption is granted.
These and other policies adopted by MIT to control the spread of Covid-19 have been informed by modeling efforts from a volunteer group of MIT faculty, students, and postdocs. The collaboration, dubbed Isolat, was co-founded by Anette “Peko” Hosoi, the Neil and Jane Pappalardo Professor of Mechanical Engineering and associate dean in the School of Engineering.
The group, which is organized through MIT’s Institute for Data, Systems, and Society (IDSS), has run numerous models to show how measures such as mask wearing, testing, ventilation, and quarantining could affect Covid-19’s spread. These models have helped to shape MIT’s Covid-19 policies throughout the pandemic, including its procedures for returning to campus this fall.
Hosoi spoke with MIT News about the data-backed reasoning behind some of these procedures, including indoor masking and regular testing, and how a “generous community” will help MIT safely weather the virus and its variants.
Q: Take us through how you have been modeling Covid-19 and its variants, in regard to helping MIT shape its Covid policies. What’s the approach you’ve taken, and why?
A: The approach we’re taking uses a simple counting exercise developed in IDSS to estimate the balance of testing, masking, and vaccination that is required to keep the virus in check. The underlying objective is to find infected people faster, on average, than they can infect others, which is captured in a simple algebraic expression. Our objective can be accomplished either by speeding up the rate of finding infected people (i.e. increasing testing frequency) or slowing down the rate of infection (i.e. increasing masking and vaccination) or by a combination of both. To give you a sense of the numbers, balances for different levels of testing are shown in the chart below for a vaccine efficacy of 67 percent and a contagious period of 18 days (which are the CDC’s latest parameters for the Delta variant).
The vertical axis shows the now-famous reproduction number R0, i.e. the average number of people that one infected person will infect throughout the course of their illness. These R0 are averages for the population, and in specific circumstances the spreading could be more than that.
Each blue line represents a different testing frequency: Below the line, the virus is controlled; above the line, it spreads. For example, the dotted blue line shows the boundary if we rely solely on vaccination with no testing. In that case, even if everyone is vaccinated, we can only control up to an R0 of about 3. Unfortunately, the CDC places R0 of the Delta variant somewhere between 5 and 9, so vaccination alone is insufficient to control the spread. (As an aside, this also means that given the efficacy estimates for the current vaccines, herd immunity is not possible.)
Next consider the dashed blue line, which represents the stability boundary if we test everyone once per week. If our vaccination rate is greater than about 90 percent, testing one time per week can control even the CDC’s most pessimistic estimate for the Delta variant’s R0.
Q: In returning to campus over the next few weeks, indoor masking and regular testing are required of every MIT community member, even those who are vaccinated. What in your modeling has shown that each of these policies is necessary?
A: Given that the chart above shows that vaccination and weekly testing are sufficient to control the virus, one should certainly ask “Why have we reinstated indoor masking?” The answer is related to the fact that, as a university, our population turns over once a year; every September we bring in a few thousand new people. Those people are coming from all over the world, and some of them may not have had the opportunity to get vaccinated yet. The good news is that MIT Medical has vaccines and will be administering them to any unvaccinated students as soon as they arrive; the bad news is that, as we all know, it takes three to five weeks for resistance to build up, depending on the vaccine. This means that we should think of August and September as a transition period during which the vaccination rates may fluctuate as new people arrive.
The other revelation that has informed our policies for September is the recent report from the CDC that infected vaccinated people carry roughly the same viral load as unvaccinated infected people. This suggests that vaccinated people — although they are highly unlikely to get seriously ill — are a consequential part of the transmission chain and can pass the virus along to others. So, in order to avoid giving the virus to people who are not yet fully vaccinated during the transition period, we all need to exercise a little extra care to give the newly vaccinated time for their immune systems to ramp up.
Q: As the fall progresses, what signs are you looking for that might shift decisions on masking and testing on campus?
A: Eventually we will have to shift responsibility toward individuals rather than institutions, and allow people to make decisions about masks and testing based on their own risk tolerance. The success of the vaccines in suppressing severe illness will enable us to shift to a position in which our objective is not necessarily to control the spread of the virus, but rather to reduce the risk of serious outcomes to an acceptable level. There are many people who believe we need to make this adjustment and wean ourselves off pandemic living. They are right; we cannot continue like this forever. However, we have not played all our cards yet, and, in my opinion, we need to carefully consider what’s left in our hand before we abdicate institutional responsibility.
The final ace we have to play is vaccinating kids. It is important to remember that we have many people in our community with kids who are too young to be vaccinated and, understandably, those parents do not want to bring Covid home to their children. Furthermore, our campus is not just a workplace; it is also home to thousands of people, some of whom have children living in our residences or attending an MIT childcare center. Given that context, and the high probability that a vaccine will be approved for children in the near future, it is my belief that our community has the empathy and fortitude to try to keep the virus in check until parents have the option to protect their children with vaccines.
Bearing in mind that children constitute an unprotected portion of our population, let me return to the original question and speculate on the fate of masks and testing in the fall. Regarding testing, the analysis suggests that we cannot give that up entirely if we would like to control the spread of the virus. Second, control of the virus is not the only benefit we get from testing. It also gives us situational awareness, serves as an early warning beacon, and provides information that individual members of the community can use as they make decisions about their own risk budget. Personally, I’ve been testing for a year now and I find it easy and reassuring. Honestly, it’s nice to know that I’m Covid-free before I see friends (outside!) or go home to my family.
Regarding masks, there is always uncertainty around whether a new variant will arise or whether vaccine efficacy will fade, but, given the current parameters and our analysis, my hope is that we will be in a position to provide some relief on the mask mandate once the incoming members of our population have been fully vaccinated. I also suspect that whenever the mask mandate is lifted, masks are not likely to go away. There are certainly situations in which I will continue to wear a mask regardless of the mandate, and many in our community will continue to feel safer wearing masks even when they are not required.
I believe that we are a generous community and that we will be willing to take precautions to help keep each other healthy. The students who were on campus last year did an outstanding job, and they have given me a tremendous amount of faith that we can be considerate and good to one another even in extremely trying times.
This fall, MIT welcomes new faculty members — five assistant professors and two tenured professors — to the departments of Biology; Chemistry; Earth, Atmospheric and Planetary Sciences; and Physics.
A physicist, Soonwon Choi is interested in dynamical phenomena that occur in strongly interacting quantum many-body systems far from equilibrium and designing their applications for quantum information science. He takes a variety of interdisciplinary approaches from analytic theory and numerical computations to collaborations on experiments with controlled quantum degrees of freedom. Recently, Choi’s research has encompassed studying the phenomenon of a phase transition in the dynamics of quantum entanglement and information, drawing on machine learning to introduce a quantum convolutional neural network that can recognize quantum states associated with a one-dimensional symmetry-protected topological phase, and exploring a range of quantum applications of the nitrogen-vacancy color center of diamond.
After completing his undergraduate study in physics at Caltech in 2012, Choi received his PhD degree in physics from Harvard University in 2018. He then worked as a Miller Postdoctoral Fellow at the University of California at Berkeley before joining the Department of Physics and the Center for Theoretical Physics as an assistant professor in July 2021.
Olivia Corradin investigates how genetic variants contribute to disease. She focuses on non-coding DNA variants — changes in DNA sequence that can alter the regulation of gene expression — to gain insight into pathogenesis. With her novel outside-variant approach, Corradin’s lab singled out a type of brain cell involved in multiple sclerosis, increasing total heritability identified by three- to five-fold. A recipient of the Avenir Award through the NIH Director’s Pioneer Award Program, Corradin also scrutinizes how genetic and epigenetic variation influence susceptibility to substance abuse disorders. These critical insights into multiple sclerosis, opioid use disorder, and other diseases have the potential to improve risk assessment, diagnosis, treatment, and preventative care for patients.
Corradin completed a bachelor’s degree in biochemistry from Marquette University in 2010 and a PhD in genetics from Case Western Reserve University in 2016. A Whitehead Institute Fellow since 2016, she also became an institute member in July 2021. The Department of Biology welcomes Corradin as an assistant professor.
Arlene Fiore seeks to understand processes that control two-way interactions between air pollutants and the climate system, as well as the sensitivity of atmospheric chemistry to different chemical, physical, and biological sources and sinks at scales ranging from urban to global and daily to decadal. Combining chemistry-climate models and observations from ground, airborne, and satellite platforms, Fiore has identified global dimensions to ground-level ozone smog and particulate haze that arise from linkages with the climate system, global atmospheric composition, and the terrestrial biosphere. She also investigates regional meteorology and climate feedbacks due to aerosols versus greenhouse gases, future air pollution responses to climate change, and drivers of atmospheric oxidizing capacity. A new research direction involves using chemistry-climate model ensemble simulations to identify imprints of climate variability on observational records of trace gases in the troposphere.
After earning a bachelor’s degree and PhD from Harvard University, Fiore held a research scientist position at the Geophysical Fluid Dynamics Laboratory and was appointed as an associate professor with tenure at Columbia University in 2011. Over the last decade, she has worked with air and health management partners to develop applications of satellite and other Earth science datasets to address their emerging needs. Fiore’s honors include the American Geophysical Union (AGU) James R. Holton Junior Scientist Award, Presidential Early Career Award for Scientists and Engineers (the highest honor bestowed by the United States government on outstanding scientists and engineers in the early stages of their independent research careers), and AGU’s James B. Macelwane Medal. The Department of Earth, Atmospheric and Planetary Sciences welcomes Fiore as the first Peter H. Stone and Paola Malanotte Stone Professor.
With a background in magnetism, Danna Freedman leverages inorganic chemistry to solve problems in physics. Within this paradigm, she is creating the next generation of materials for quantum information by designing spin-based quantum bits, or qubits, based in molecules. These molecular qubits can be precisely controlled, opening the door for advances in quantum computation, sensing, and more. She also harnesses high pressure to synthesize new emergent materials, exploring the possibilities of intermetallic compounds and solid-state bonding. Among other innovations, Freedman has realized millisecond coherence times in molecular qubits, created a molecular analogue of an NV center featuring optical read-out of spin, and discovered the first iron-bismuth binary compound.
Freedman received her bachelor’s degree from Harvard University and her PhD from the University of California at Berkeley, then conducted postdoctoral research at MIT before joining the faculty at Northwestern University as an assistant professor in 2012, earning an NSF CAREER Award, the Presidential Early Career Award for Scientists and Engineers, the ACS Award in Pure Chemistry, and more. She was promoted to associate professor in 2018 and full professor with tenure in 2020. Freedman returns to MIT as the Frederick George Keyes Professor of Chemistry.
Kristin Knouse PhD ’17 aims to understand how tissues sense and respond to damage, with the goal of developing new approaches for regenerative medicine. She focuses on the mammalian liver — which has the unique ability to completely regenerate itself — to ask how organisms react to organ injury, how certain cells retain the ability to grow and divide while others do not, and what genes regulate this process. Knouse creates innovative tools, such as a genome-wide CRISPR screening within a living mouse, to examine liver regeneration from the level of a single-cell to the whole organism.
Knouse received a bachelor’s degree in biology from Duke University in 2010 and then enrolled in the Harvard and MIT MD-PhD Program, where she earned a PhD through the MIT Department of Biology in 2016 and an MD through the Harvard-MIT Program in Health Sciences and Technology in 2018. In 2018, she established her independent laboratory at the Whitehead Institute for Biomedical Research and was honored with the NIH Director’s Early Independence Award. Knouse joins the Department of Biology and the Koch Institute for Integrative Cancer Research as an assistant professor.
Lina Necib PhD ’17 is an astroparticle physicist exploring the origin of dark matter through a combination of simulations and observational data that correlate the dynamics of dark matter with that of the stars in the Milky Way. She has investigated the local dynamic structures in the solar neighborhood using the Gaia satellite, contributed to building a catalog of local accreted stars using machine learning techniques, and discovered a new stream called Nyx, after the Greek goddess of the night. Necib is interested in employing Gaia in conjunction with other spectroscopic surveys to understand the dark matter profile in the local solar neighborhood, the center of the galaxy, and in dwarf galaxies.
After obtaining a bachelor’s degree in mathematics and physics from Boston University in 2012 and a PhD in theoretical physics from MIT in 2017, Necib was a Sherman Fairchild Fellow at Caltech, a Presidential Fellow at the University of California at Irvine, and a fellow in theoretical astrophysics at Carnegie Observatories. She returns to MIT as an assistant professor in the Department of Physics and a member of the MIT Kavli Institute for Astrophysics and Space Research.
Andrew Vanderburg studies exoplanets, or planets that orbit stars other than the sun. Conducting astronomical observations from Earth as well as space, he develops cutting-edge methods to learn about planets outside of our solar system. Recently, he has leveraged machine learning to optimize searches and identify planets that were missed by previous techniques. With collaborators, he discovered the eighth planet in the Kepler-90 solar system, a Jupiter-like planet with unexpectedly close orbiting planets, and rocky bodies disintegrating near a white dwarf, providing confirmation of a theory that such stars may accumulate debris from their planetary systems.
Vanderburg received a bachelor’s degree in physics and astrophysics from the University of California at Berkeley in 2013 and a PhD in Astronomy from Harvard University in 2017. Afterward, Vanderburg moved to the University of Texas at Austin as a NASA Sagan Postdoctoral Fellow, then to the University of Wisconsin at Madison as a faculty member. He joins MIT as an assistant professor in the Department of Physics and a member of the Kavli Institute for Astrophysics and Space Research.
In fall 2019, a new class, 6.S898/12.S992 (Climate Change Seminar), arrived at MIT. It was, at the time, the only course in the Department of Electrical Engineering and Computer Science (EECS) to tackle the science of climate change. The class covered climate models and simulations alongside atmospheric science, policy, and economics.
Ron Rivest, MIT Institute Professor of Computer Science, was one of the class’s three instructors, with Alan Edelman of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and John Fernández of the Department of Urban Studies and Planning. “Computer scientists have much to contribute to climate science,” Rivest says. “In particular, the modeling and simulation of climate can benefit from advances in computer science.”
Rivest is one of many MIT faculty members who have been working in recent years to bring topics in climate, sustainability, and the environment to students in a growing variety of fields. And students have said they want this trend to continue.
“Sustainability is something that touches all disciplines,” says Megan Xu, a rising senior in biological engineering and advisory chair of the Undergraduate Association Sustainability Committee. “As students who have grown up knowing that climate change is real and witnessed climate disaster after disaster, we know this is a huge problem that needs to be addressed by our generation.”
Expanding the course catalog
As education program manager at the MIT Environmental Solutions Initiative, Sarah Meyers has repeatedly had a hand in launching new sustainability classes. She has steered grant money to faculty, brought together instructors, and helped design syllabi — all in the service of giving MIT students the same world-class education in climate and sustainability that they get in science and engineering.
Her work has given Meyers a bird’s-eye view of MIT’s course offerings in this area. By her count, there are now over 120 undergraduate classes, across 23 academic departments, that teach climate, environment, and sustainability principles.
“Educating the next generation is the most important way that MIT can have an impact on the world’s environmental challenges,” she says. “MIT students are going to be leaders in their fields, whatever they may be. If they really understand sustainable design practices, if they can balance the needs of all stakeholders to make ethical decisions, then that actually changes the way our world operates and can move humanity towards a more sustainable future.”
Some sustainability classes are established institutions at MIT. Success stories include 2.00A (Fundamentals of Engineering Design: Explore Space, Sea and Earth), a hands-on engineering class popular with first-year students; and 21W.775 (Writing About Nature and Environmental Issues), which has helped undergraduates fulfill their HASS-H (humanities distribution subject) and CI-H (Communication Intensive subject in the Humanities, Arts, and Social Sciences) graduation requirements for 15 years.
Expanding this list of classes is an institutional priority. In the recently released Climate Action Plan for the Decade, MIT pledged to recruit at least 20 additional faculty members who will teach climate-related classes.
“I think it's easy to find classes if you're looking for sustainability classes to take,” says Naomi Lutz, a senior in mechanical engineering who helped advise the MIT administration on education measures in the Climate Action Plan. “I usually scroll through the titles of the classes in courses 1, 2, 11, and 12 to see if any are of interest. I also have used the Environment & Sustainability Minor class list to look for sustainability-related classes to take.
“The coming years are critical for the future of our planet, so it's important that we all learn about sustainability and think about how to address it,” she adds.
Working with students’ schedules
Still, despite all this activity, climate and sustainability are not yet mainstream parts of an MIT education. Last year, a survey of over 800 MIT undergraduates, taken by the Undergraduate Association Sustainability Committee, found that only one in four had ever taken a class related to sustainability. But it doesn’t seem to be from lack of interest in the topic. More than half of those surveyed said that sustainability is a factor in their career planning, and almost 80 percent try to practice sustainability in their daily lives.
“I’ve often had conversations with students who were surprised to learn there are so many classes available,” says Meyers. “We do need to do a better job communicating about them, and making it as easy as possible to enroll.”
A recurring challenge is helping students fit sustainability into their plans for graduation, which are often tightly mapped-out.
“We each only have four years — around 32 to 40 classes — to absorb all that we can from this amazing place,” says Xu. “Many of these classes are mandated to be GIRs [General Institute Requirements] and major requirements. Many students recognize that sustainability is important, but might not have the time to devote an entire class to the topic if it would not count toward their requirements.”
This was a central focus for the students who were involved in forming education recommendations for the Climate Action Plan. “We propose that more sustainability-related courses or tracks are offered in the most common majors, especially in Course 6 [EECS],” says Lutz. “If students can fulfill major requirements while taking courses that address environmental problems, we believe more students will pursue research and careers related to sustainability.”
She also recommends that students look into the dozens of climate and sustainability classes that fulfill GIRs. “It’s really easy to take sustainability-related courses that fulfill HASS [Humanities, Arts, and Social Sciences] requirements,” she says. For example, students can meet their HASS-S (social sciences sistribution subject) requirement by taking 21H.185 (Environment and History), or fulfill their HASS-A requirement with CMS.374 (Transmedia Art, Extraction and Environmental Justice).
Classes with impact
For those students who do seek out sustainability classes early in their MIT careers, the experience can shape their whole education.
“My first semester at MIT, I took Environment and History, co-taught by professors Susan Solomon and Harriet Ritvo,” says Xu. “It taught me that there is so much more involved than just science and hard facts to solving problems in sustainability and climate. I learned to look at problems with more of a focus on people, which has informed much of the extracurricular work that I’ve gone on to do at MIT.”
And the faculty, too, sometimes find that teaching in this area opens new doors for them. Rivest, who taught the climate change seminar in Course 6, is now working to build a simplified climate model with his co-instructor Alan Edelman, their teaching assistant Henri Drake, and Professor John Deutch of the Department of Chemistry, who joined the class as a guest lecturer. “I very much enjoyed meeting new colleagues from all around MIT,” Rivest says. “Teaching a class like this fosters connections between computer scientists and climate scientists.”
Which is why Meyers will continue helping to get these classes off the ground. “We know students think climate is a huge issue for their futures. We know faculty agree with them,” she says. “Everybody wants this to be part of an MIT education. The next step is to really reach out to students and departments to fill the classrooms. That’s the start of a virtuous cycle where enrollment drives more sustainability instruction in every part of MIT.”
Routing is one of the most studied problems in operations research; even small improvements in routing efficiency can save companies money and result in energy savings and reduced environmental impacts. Now, three teams of researchers from universities around the world have received prize money totaling $175,000 for their innovative route optimization models.
The three teams were the winners of the Amazon Last-Mile Routing Research Challenge, through which the MIT Center for Transportation & Logistics (MIT CTL) and Amazon engaged with a global community of researchers across a range of disciplines, from computer science to business operations to supply chain management, challenging them to build data-driven route optimization models leveraging massive historical route execution data.
First announced in February, the research challenge attracted more than 2,000 participants from around the world. Two hundred twenty-nine researcher teams formed during the spring to independently develop solutions that incorporated driver know-how into route optimization models with the intent that they would outperform traditional optimization approaches. Out of the 48 teams whose models qualified for the final round of the challenge, three teams’ work stood out above the rest. Amazon provided real operational training data for the models and evaluated submissions, with technical support from MIT CTL scientists.
In real life, drivers frequently deviate from planned and mathematically optimized route sequences. Drivers carry information about which roads are hard to navigate when traffic is bad, when and where they can easily find parking, which stops can be conveniently served together, and many other factors that existing optimization models simply don’t capture.
Each model addressed the challenge data in a unique way. The methodological approaches chosen by the participants frequently combined traditional exact and heuristic optimization approaches with nontraditional machine learning methods. On the machine learning side, the most commonly adopted methods were different variants of artificial neural networks, as well as inverse reinforcement learning approaches.
There were 45 submissions that reached the finalist phase, with team members hailing from 29 countries. Entrants spanned all levels of higher education from final-year undergraduate students to retired faculty. Entries were assessed in a double-blind review process so that the judges would not know what team was attached to each entry.
The third-place prize of $25,000 was awarded to Okan Arslan and Rasit Abay. Okan is a professor at HEC Montréal, and Rasit is a doctoral student at the University of New South Wales in Australia. The runner-up prize at $50,000 was awarded to MIT’s own Xiaotong Guo, Qingyi Wang, and Baichuan Mo, all doctoral students. The top prize of $100,000 was awarded to Professor William Cook of the University of Waterloo in Canada, Professor Stephan Held of the University of Bonn in Germany, and Professor Emeritus Keld Helsgaun of Roskilde University in Denmark. Congratulations to all winners and contestants were held via webinar on July 30.
Top-performing teams may be interviewed by Amazon for research roles in the company’s Last Mile organization. MIT CTL will publish and promote short technical papers written by all finalists and might invite top-performing teams to present at MIT. Further, a team led by Matthias Winkenbach, director of the MIT Megacity Logistics Lab, will guest-edit a special issue of Transportation Science, one of the most renowned academic journals in this field, featuring academic papers on topics related to the problem tackled by the research challenge.
Work on MIT’s Strategic Action Plan for Diversity, Equity, and Inclusion started last fall, and the plan’s first draft was released in late March 2020. Powered by inputs and feedback from three dozen community engagement sessions and a steady stream of email responses from students, staff, faculty, postdocs, alumni, and others, the plan is being revised and updated over the summer with hopes for a fall release. The development of the strategic plan is being led by Institute Community and Equity Officer John Dozier, along with Deputy ICEO Maryanne Kirkbride and Associate Provost Tim Jamison.
In a recent conversation prepared for MIT News, Vice President for Research Maria Zuber described how she wants the plan to help MIT attract and support postdoctoral scholars from a broad range of backgrounds. Increasing diversity in this community, she notes, will have positive effects for all of academia.
Q: What are the opportunities and challenges specific to your role as vice president for research in trying to advance a strategic plan for diversity, equity, and inclusion at MIT?
A: As the vice president for research, I oversee a number of interdisciplinary labs and centers; I’m responsible for research administration and policy, including the terrific staff that ensures our research enterprise runs smoothly; and I oversee MIT Postdoctoral Services, which endeavors to improve the experiences of the 1,500 postdocs who come to MIT for advanced training and play a key role in the research community.
As I go about this work, the opportunity always comes back to a simple question: How can we best achieve MIT’s mission? Our mission says that we want everyone at MIT to have “the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.”
For that to happen, every member of the community needs to be able to take prudent risks, make mistakes, try new approaches to solving old problems, and bring their own unique perspectives to bear on hard questions. And there’s just no way that people will feel truly comfortable doing those things if they’re not sure they have a place here. If you’re not sure that you belong, then you’re more likely to keep your head down, avoid risk-taking, and go with the flow. That’s not optimal for anyone. To provide an environment where a diverse community of people can do its best, leading-edge work — that is an immense opportunity.
A challenge, and President Reif has pointed this out before, is MIT’s decentralized structure — it’s core to our culture and it’s a key ingredient in our success. But it also makes it harder to ensure that the experience is welcoming and equitable for everyone across campus. It’s a fact we need to contend with if we want a coordinated and consistent set of practices for attracting, retaining, and developing a diverse faculty and staff, including postdocs, across the Institute. I want to be clear that this is a challenge to be addressed — not an excuse for inaction.
Q: How do you think the plan will impact the lives of MIT community members, most especially postdocs?
A: Postdocs come to MIT from many different countries and backgrounds. No matter who they are or where they come from, we want them to feel supported to do their best work — scholarship that will advance their careers and help solve pressing challenges.
The most significant factor in the experience of postdocs at MIT is their relationship with their principal investigator. That’s why the strategic plan includes a focus on training and learning opportunities for PIs, so they can incorporate an understanding of the value of diversity, equity, and inclusion into their hiring and team-management practices. Understanding and helping to improve postdoctoral hiring practices will be an important area of focus for the director of diversity, equity, and inclusion in my office — a newly created role that we will fill in the coming months. We’re also working to improve our orientation and onboarding for postdocs, and to provide them with improved mentorship opportunities.
Finally, as I often say: “Show me your data.” If we really want to increase the number of postdocs from underrepresented groups, ensure a consistently productive experience for each of them, and set them on a path to career success no matter their background, then improvements to training for PIs or new onboarding programs is not enough. We also need more robust data collection and analysis so we can assess whether our efforts are having the intended effect and then hold ourselves accountable to ensure continued improvements.
Q: What do you think will be the most important outcome of the plan?
A: We will accelerate progress.
A personal mission of mine for many years has been to increase the representation of women in the sciences. When I first arrived at MIT, the proportion of women faculty in the School of Science was about 8 percent — and it had not changed for at least a decade. I went on to become the first woman to head a science department at MIT, and recent research has found that in my field, the geosciences, the proportion of women in faculty positions at 62 U.S. universities has been on the rise for two decades. But even today women account for just one in five full professors in the geosciences at those universities. That’s progress, but it’s not enough.
In some respects, our community of postdocs is wonderfully diverse. They come from all over the world, and there’s no question that the intellectual life of our campus benefits from that breadth of experiences and perspectives. In other respects, however, we have a lot of work to do. Our community of postdocs from the United States does not represent the diversity of the country as a whole. And since today’s postdocs are often tomorrow’s faculty members, this underrepresentation is perpetuated as people rise through academia’s ranks.
With focused resources, renewed accountability, enhanced expertise, and a whole-of-MIT approach, the most important outcome of this plan will be more progress, faster — the kind of progress that you can see and feel.
Creating a good customer experience increasingly means creating a good digital experience. But metrics like pageviews and clicks offer limited insight into how much customers actually like a digital product.
That’s the problem the digital optimization company Amplitude is solving. Amplitude gives companies a clearer picture into how users interact with their digital products to help them understand exactly which features to promote or improve.
“It’s all about using product data to drive your business,” says Amplitude CEO Spenser Skates ’10, who co-founded the company with Curtis Liu ’10 and Stanford University graduate Jeffrey Wang. “Mobile apps and websites are really complex. The average app or website will have thousands of things you can do with it. The question is how you know which of those things are driving a great user experience and which parts are really frustrating for users.”
Amplitude’s database can gather millions of details about how users behave inside an app or website and allow customers to explore that information without needing data science degrees.
“It provides an interface for very easy, accessible ways of looking at your data, understanding your data, and asking questions of that data,” Skates says.
Amplitude, which recently announced it will be going public, is already helping 23 of the 100 largest companies in the U.S. Customers include media companies like NBC, tech companies like Twitter, and retail companies like Walmart.
“Our platform helps businesses understand how people are using their apps and websites so they can create better versions of their products,” Skates says. “It’s all about creating a really compelling product.”
The founders say their years at MIT were among the best of their lives. Skates and Liu were undergraduates from 2006 to 2010. Skates majored in biological engineering while Liu majored in mathematics and electrical engineering and computer science. The two first met as opponents in MIT’s Battlecode competition, in which students use artificial intelligence algorithms to control teams of robots that compete in a strategy game against other teams. The following year they teamed up.
“There are a lot of parallels between what you’re trying to do in Battlecode and what you end up having to do in the early stages of a startup,” Liu says. “You have limited resources, limited time, and you’re trying to accomplish a goal. What we found is trying a lot of different things, putting our ideas out there and testing them with real data, really helped us focus on the things that actually mattered. That method of iteration and continual improvement set the foundation for how we approach building products and startups.”
Liu and Skates next participated in the MIT $100K Entrepreneurship Competition with an idea for a cloud-based music streaming service. After graduation, Skates began working in finance and Liu got a job at Google, but they continued pursuing startup ideas on the side, including a website that let alumni see where their classmates ended up and a marketplace for finding photographers.
A year after graduation, the founders decided to quit their jobs and work on a startup full time. Skates moved into Liu’s apartment in San Francisco, setting up a mattress on the floor, and they began working on a project that became Sonalight, a voice recognition app. As part of the project, the founders built an internal system to understand where users got stuck in the app and what features were used the most.
Despite getting over 100,000 downloads, the founders decided Sonalight was a little too early for its time and started thinking their analytics feature could be useful to other companies. They spoke with about 30 different product teams to learn more about what companies wanted from their digital analytics. Amplitude was officially founded in 2012.
Amplitude gathers fine details about digital product usage, parsing out individual features and actions to give customers a better view of how their products are being used. Using the data in Amplitude’s intuitive, no-code interface, customers can make strategic decisions like whether to launch a feature or change a distribution channel.
The platform is designed to ease the bottlenecks that arise when executives, product teams, salespeople, and marketers want to answer questions about customer experience or behavior but need the data science team to crunch the numbers for them.
“It’s a very collaborative interface to encourage customers to work together to understand how users are engaging with their apps,” Skates says.
Amplitude’s database also uses machine learning to segment users, predict user outcomes, and uncover novel correlations. Earlier this year, the company unveiled a service called Recommend that helps companies create personalized user experiences across their entire platform in minutes. The service goes beyond demographics to personalize customer experiences based on what users have done or seen before within the product.
“We’re very conscious on the privacy front,” Skates says. “A lot of analytics companies will resell your data to third parties or use it for advertising purposes. We don’t do any of that. We’re only here to provide product insights to our customers. We’re not using data to track you across the web. Everyone expects Netflix to use the data on what you’ve watched before to recommend what to watch next. That’s effectively what we’re helping other companies do.”
Optimizing digital experiences
The meditation app Calm is on a mission to help users build habits that improve their mental wellness. Using Amplitude, the company learned that users most often use the app to get better sleep and reduce stress. The insights helped Calm’s team double down on content geared toward those goals, launching “sleep stories” to help users unwind at the end of each day and adding content around anxiety relief and relaxation. Sleep stories are now Calm’s most popular type of content, and Calm has grown rapidly to millions of people around the world.
Calm’s story shows the power of letting user behavior drive product decisions. Amplitude has also helped the online fundraising site GoFundMe increase donations by showing users more compelling campaigns and the exercise bike company Peloton realize the importance of social features like leaderboards.
Moving forward, the founders believe Amplitude’s platform will continue helping companies adapt to an increasingly digital world in which users expect more compelling, personalized experiences.
“If you think about the online experience for companies today compared to 10 years ago, now [digital] is the main point of contact, whether you’re a media company streaming content, a retail company, or a finance company,” Skates says. “That’s only going to continue. That’s where we’re trying to help.”
Laurence Young, professor emeritus of astronautics and renowned expert in bioastronautics, dies at 85
Laurence R. Young '57, SM '59, ScD '62, the Apollo Program Professor Emeritus of Astronautics and professor of health sciences and technology at MIT, died peacefully at his home in Cambridge, Massachusetts, on Aug. 4 after a long illness. He was 85.
A longtime member of the MIT community, Young was widely regarded for his pioneering role in the field of bioastronautics, the study of the impact of the space environment on living organisms, focusing in particular on the human factors of spaceflight. Many biological systems processes that comprise and govern the human body — from bones and muscles to cardiovascular regulation and sensory-motor control — depend on Earth's gravity to function properly. To protect astronauts from potentially negative effects of weightlessness, radiation, and psychological stress encountered in space, developing artificial life support systems for human protection is vital for future missions.
Young joined the faculty in the Department of Aeronautics and Astronautics (AeroAstro) at MIT in 1962. There, he co-founded the Man-Vehicle Laboratory (now the Human-Systems Laboratory) with Y.T. Li to conduct his research on the visual and vestibular systems, visual-vestibular interaction, flight simulation, space motion sickness, and manual control and displays.
"Larry was one of the first engineers to introduce math modeling techniques to aerospace-relevant areas of physiology and human factors. He knew that the quantitative approach would lead to new insights, so he started with eye movements and then moved on to perception," says Charles Oman, senior research engineer of aeronautics and astronautics at MIT and longtime colleague of Young. "I still remember in those days, some skeptics said perceptions were too complicated to model, but he proved them all wrong, and in the process, revolutionized the fields of vestibular physiology and flight simulation. His success and enthusiasm for his work were infectious."
Young was born in New York City on December 19, 1935 to Benjamin and Bess Young. After graduating from the Bronx High School of Science in 1952, Young received a BA from Amherst College in 1957; a certificate in applied mathematics from the Sorbonne, Paris as a French Government Fellow in 1958; BS and MS degrees in electrical engineering and an ScD in instrumentation from MIT in 1962.
Young's career extended beyond MIT to the national and international stage; he consulted with NASA’s Marshall Spaceflight Center on the Apollo project and later became a qualified payload specialist for the U.S. space shuttle's Spacelab biological laboratory in 1993. While he never flew a space mission, he served as backup crew (alternate payload specialist) on Spacelab Life Sciences-2 (STS-58) and was principal or co-investigator on seven shuttle missions conducting human orientation experiments.
Throughout various points during his career, Young held visiting professor positions at ETH (Swiss Federal Institute of Technology); the Zurich Kantonsspital; the Conservatoire des Arts et Metiers in Paris; the College de France, Paris; the Universite de Provence, Marseille; and Stanford University. Notably, Young also founded National Space Biomedical Research Institute, serving as director from 1997 to 2001.
Closer to home, Young served as director of the Massachusetts Space Grant Consortium; launched the Harvard-MIT Program in Health Sciences and Technology (HST) doctoral program in bioastronautics; and after retiring in 2013, remained active in AeroAstro, serving as a senior advisor lending his expertise on the department’s 2020 strategic plan committee. The MIT Institute for Medical Engineering and Science (IMES) is HST’s home at MIT.
“Larry was amazing at everything he did — he loved MIT in practice and in concept, always promoting his students above himself and forever asking what would make our school better able to change the world. As founding member of HST and bedrock of IMES, his ideas have forever changed how we teach and how we bridge engineering and medicine,” says Elazer Edelman, the Edward J. Poitras Professor in Medical Engineering and Science, director of IMES, and a practicing cardiologist at Brigham and Women’s Hospital. “His scientific and educational reforms made the universe more accessible and our world safer and healthier, creating new communities of scholars, new fields of studies like biomedical engineering and new leaders. His life affected every living person and at the same time touched each of those he met personally on an individual level.”
In tandem with his extensive contributions to research, Young is remembered for the widespread dissemination of his knowledge through his impact as a teacher. Young mentored many colleagues when they were students, including (but not limited to) Oman, Edelman, and Professor David Mindell — with whom he would later develop the highly popular course STS.471J / 16.895J / ESD.30J (Engineering Apollo). Many of Young's mentees would become influential members of aerospace academia and industry in their own right; these include NASA astronaut and moonwalker Charlie Duke.
"I literally can't count the thousands of students and alumni that Larry touched, myself among them. Recently, Larry led the charge to compose a handbook of bioastronautics, leaving us with the encyclopedic knowledge so future generations will continue with this work," says Dava Newman, the Apollo Professor of Astronautics, director of the MIT Media Lab, HST affiliate, and former Young mentee. "With all of the science we've learned and through all his years of mentoring, the moonshot Larry leaves with us is to never think about any constraints and boundaries, to literally always shoot for the moon, to Mars and beyond — that's the big dream that he inspired in me and all of his colleagues."
Throughout his career, Young received extensive recognition for his contributions, service, and leadership to the aerospace field. He was elected to the National Academy of Engineering and the Institute of Medicine of the National Academy of Sciences and a full member of the International Academy of Astronautics. He served on numerous academy committees and chaired NASA's Innovative Advanced Concepts External Council. He held fellowships with the Institute of Electrical and Electronics Engineers, the Biomedical Engineering Society, the American Institute of Medical and Biological Engineering, and the Explorers Club. In 1992, he was among the recipients recognized with the American Institute of Aeronautics and Astronautics (AIAA) Jeffries Award "for outstanding contributions to space biology and medicine as a principal investigator on the Spacelab Life Sciences 1 mission." In 1995, NASA recognized his achievements with a Space Act Award for his development of an expert system for astronauts. In 1998, he received the prestigious Koetser Foundation Prize in Zurich for his contributions to neuroscience. In 2013, he received the Pioneer Award from the National Space Biomedical Research Institute. In 2018, he received the AIAA de Florez Award for Flight Simulation, and the Aerospace Medical Association's Professional Excellence Award for Lifetime Contributions.
Outside of his career as an engineer, Young was an avid skier, which led him to become active in ski injury research. He was a director of the International Society for Skiing Safety and chaired the Ski Injury Statistics Subcommittee of the American Society for Testing and Materials Committee on Snow Skiing before being elected committee chair in 1987. He received the United States Ski Association Award of Merit and the Best Research Paper Award from the American Academy of Orthopedic Surgeons.
In addition to countless alumni, colleagues, and friends, Young is survived by his beloved wife Vicki Goldberg; his sister Ellen Rosenberg; children Eliot Young SM ’87, SM ’90, ScD ’93; Leslie Young PhD ’94; and Robert Young; his first wife and the mother of his children Jody Williams; and grandchildren Joshua Young, Evan Young, David Young, Alexander Young, and Rachel Young.
A randomized evaluation of a nationwide information campaign on Facebook found that short messages from physicians and nurses had a significant impact on reducing holiday travel and decreasing subsequent Covid-19 infection rates. Researchers found that the campaign, which reached almost 30 million Facebook users, was an impactful and cost-effective way to slow the spread of Covid-19 and enact behavior change.
This study was designed by an interdisciplinary research team, based on a growing body of literature on the effectiveness of physicians as public health messengers, to test how these messages would work at scale. The research team includes academics from MIT, Harvard University, Massachusetts General Hospital, Online Care Group, Stanford University, Ludwig Maximilian University of Munich, Bozeman Health Deaconess Hospital, Yale University, Lynn Community Health Center, Johns Hopkins University, St. Anthony North Family Medicine, Paris School of Economics, and McGovern Medical School at the University of Texas.
Based on public guidance from the U.S. Centers for Disease Control and Prevention (CDC) urging people not to travel for the 2020 holidays, the campaign featured short messages from physicians and nurses encouraging viewers to stay at home in the lead-up to Thanksgiving and Christmas to prevent the spread of Covid-19. Across 13 states, Facebook subscribers in randomly selected ZIP codes in 820 counties in the United States were assigned to receive 20-second messages as sponsored content at varying amounts. On average, each user included in this study received two to three videos at Thanksgiving and three to four videos at Christmas.
In counties where a larger proportion of ZIP codes received high-coverage Facebook ads, the average distance traveled decreased by nearly one percentage point in the three days leading up to the holidays (a decrease was not detected on the day of each holiday). In the two-week period starting five days post-holiday (the average incubation time for Covid-19), Covid-19 cases declined 3.5 percent. This effect was not impacted by geographic or political demographics. The bipartisan nature of the campaign’s impact demonstrates the importance of public health campaigns that rely on trusted figures.
The success of this program provides a clear example of the impact that social media can have on public health. Almost 70 percent of Americans are on Facebook, and about 36 percent report getting their news predominantly from the platform. This suggests that Facebook has the potential to be an effective and impactful public health tool for disseminating accurate public health messages to a vast audience, the researchers say.
Esther Duflo, the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at MIT, co-founder and director of MIT’s Abdul Latif Jameel Poverty Action Lab, and a senior author of the study, notes, “These findings demonstrate that informing people of relevant public health information can not only change behaviors, it can save lives. By relying on both the public trust in health-care workers and the widespread use of social media, campaigns such as these can make a significant contribution to addressing Covid-19 and future health crises.”
This work has important implications for preventing the spread of future pandemics as well as more salient applications amid growing concerns over Covid-19 variants and persistent resistance to vaccinations. Additional research is ongoing to assess how similar messaging campaigns delivered via social media may be able to encourage Covid-19 vaccination in the United States.
Pavements are an abundant urban surface, covering around 40 percent of American cities. But in addition to carrying traffic, they can also emit heat.
Due to what’s called the urban heat island effect, densely built, impermeable surfaces like pavements can absorb solar radiation and warm up their surroundings by re-emitting that radiation as heat. This phenomenon poses a serious threat to cities. It increases air temperatures by up as much as 7 degrees Fahrenheit and contributes to health and environmental risks — risks that climate change will magnify.
In response, researchers at the MIT Concrete Sustainability Hub (MIT CSHub) are studying how a surface that ordinarily heightens urban heat islands can instead lessen their intensity. Their research focuses on “cool pavements,” which reflect more solar radiation and emit less heat than conventional paving surfaces.
A recent study by a team of current and former MIT CSHub researchers in the journal of Environmental Science and Technology outlines cool pavements and their implementation. The study found that they could lower air temperatures in Boston and Phoenix by up to 1.7 degrees Celsius (3 F) and 2.1 C (3.7 F), respectively. They would also reduce greenhouse gas emissions, cutting total emissions by up to 3 percent in Boston and 6 percent in Phoenix. Achieving these savings, however, requires that cool pavement strategies be selected according to the climate, traffic, and building configurations of each neighborhood.
Cities like Los Angeles and Phoenix have already conducted sizeable experiments with cool pavements, but the technology is still not widely implemented. The CSHub team hopes their research can guide future cool paving projects to help cities cope with a changing climate.
Scratching the surface
It’s well known that darker surfaces get hotter in sunlight than lighter ones. Climate scientists use a metric called “albedo” to help describe this phenomenon.
“Albedo is a measure of surface reflectivity,” explains Hessam AzariJafari, the paper’s lead author and a postdoc at the MIT CSHub. “Surfaces with low albedo absorb more light and tend to be darker, while high-albedo surfaces are brighter and reflect more light.”
Albedo is central to cool pavements. Typical paving surfaces, like conventional asphalt, possess a low albedo and absorb more radiation and emit more heat. Cool pavements, however, have brighter materials that reflect more than three times as much radiation and, consequently, re-emit far less heat.
“We can build cool pavements in many different ways,” says Randolph Kirchain, a researcher in the Materials Science Laboratory and co-director of the Concrete Sustainability Hub. “Brighter materials like concrete and lighter-colored aggregates offer higher albedo, while existing asphalt pavements can be made ‘cool’ through reflective coatings.”
CSHub researchers considered these several options in a study of Boston and Phoenix. Their analysis considered different outcomes when concrete, reflective asphalt, and reflective concrete replaced conventional asphalt pavements — which make up more than 95 percent of pavements worldwide.
For a comprehensive understanding of the environmental benefits of cool pavements in Boston and Phoenix, researchers had to look beyond just paving materials. That’s because in addition to lowering air temperatures, cool pavements exert direct and indirect impacts on climate change.
“The one direct impact is radiative forcing,” notes AzariJafari. “By reflecting radiation back into the atmosphere, cool pavements exert a radiative forcing, meaning that they change the Earth’s energy balance by sending more energy out of the atmosphere — similar to the polar ice caps.”
Cool pavements also exert complex, indirect climate change impacts by altering energy use in adjacent buildings.
“On the one hand, by lowering temperatures, cool pavements can reduce some need for AC [air conditioning] in the summer while increasing heating demand in the winter,” says AzariJafari. “Conversely, by reflecting light — called incident radiation — onto nearby buildings, cool pavements can warm structures up, which can increase AC usage in the summer and lower heating demand in the winter.”
What’s more, albedo effects are only a portion of the overall life cycle impacts of a cool pavement. In fact, impacts from construction and materials extraction (referred to together as embodied impacts) and the use of the pavement both dominate the life cycle. The primary use phase impact of a pavement — apart from albedo effects — is excess fuel consumption: Pavements with smooth surfaces and stiff structures cause less excess fuel consumption in the vehicles that drive on them.
Assessing the climate-change impacts of cool pavements, then, is an intricate process — one involving many trade-offs. In their study, the researchers sought to analyze and measure them.
A full reflection
To determine the ideal implementation of cool pavements in Boston and Phoenix, researchers investigated the life cycle impacts of shifting from conventional asphalt pavements to three cool pavement options: reflective asphalt, concrete, and reflective concrete.
To do this, they used coupled physical simulations to model buildings in thousands of hypothetical neighborhoods. Using this data, they then trained a neural network model to predict impacts based on building and neighborhood characteristics. With this tool in place, it was possible to estimate the impact of cool pavements for each of the thousands of roads and hundreds of thousands of buildings in Boston and Phoenix.
In addition to albedo effects, they also looked at the embodied impacts for all pavement types and the effect of pavement type on vehicle excess fuel consumption due to surface qualities, stiffness, and deterioration rate.
After assessing the life cycle impacts of each cool pavement type, the researchers calculated which material — conventional asphalt, reflective asphalt, concrete, and reflective concrete — benefited each neighborhood most. They found that while cool pavements were advantageous in Boston and Phoenix overall, the ideal materials varied greatly within and between both cities.
“One benefit that was universal across neighborhood type and paving material, was the impact of radiative forcing,” notes AzariJafari. “This was particularly the case in areas with shorter, less-dense buildings, where the effect was most pronounced.”
Unlike radiative forcing, however, changes to building energy demand differed by location. In Boston, cool pavements reduced energy demand as often as they increased it across all neighborhoods. In Phoenix, cool pavements had a negative impact on energy demand in most census tracts due to incident radiation. When factoring in radiative forcing, though, cool pavements ultimately had a net benefit.
Only after considering embodied emissions and impacts on fuel consumption did the ideal pavement type manifest for each neighborhood. Once factoring in uncertainty over the life cycle, researchers found that reflective concrete pavements had the best results, proving optimal in 53 percent and 73 percent of the neighborhoods in Boston and Phoenix, respectively.
Once again, uncertainties and variations were identified. In Boston, replacing conventional asphalt pavements with a cool option was always preferred, while in Phoenix concrete pavements — reflective or not — had better outcomes due to rigidity at high temperatures that minimized vehicle fuel consumption. And despite the dominance of concrete in Phoenix, in 17 percent of its neighborhoods all reflective paving options proved more or less as effective, while in 1 percent of cases, conventional pavements were actually superior.
“Though the climate change impacts we studied have proven numerous and often at odds with each other, our conclusions are unambiguous: Cool pavements could offer immense climate change mitigation benefits for both cities,” says Kirchain.
The improvements to air temperatures would be noticeable: the team found that cool pavements would lower peak summer air temperatures in Boston by 1.7 C (3 F) and in Phoenix by 2.1 C (3.7 F). The carbon dioxide emissions reductions would likewise be impressive. Boston would decrease its carbon dioxide emissions by as much as 3 percent over 50 years while reductions in Phoenix would reach 6 percent over the same period.
This analysis is one of the most comprehensive studies of cool pavements to date — but there’s more to investigate. Just as with pavements, it’s also possible to adjust building albedo, which may result in changes to building energy demand. Intensive grid decarbonization and the introduction of low-carbon concrete mixtures may also alter the emissions generated by cool pavements.
There’s still lots of ground to cover for the CSHub team. But by studying cool pavements, they’ve elevated a brilliant climate change solution and opened avenues for further research and future mitigation.
The MIT Concrete Sustainability Hub is a team of researchers from several departments across MIT working on concrete and infrastructure science, engineering, and economics. Its research is supported by the Portland Cement Association and the Ready Mixed Concrete Research and Education Foundation.
After a summer of billionaires in space, many people have begun to wonder when they will get their turn. The cost of entering space is currently too high for the average citizen, but the work of PhD candidate Martin Nisser may help change that. His work on self-assembling robots could be key to reducing the costs that help determine the price of a ticket.
Nisser’s fascination with engineering has been a consistent theme throughout a life filled with change. Born to Swedish parents, he spent a decade in Greece before moving to the UAE, and eventually to Scotland for his undergraduate degree. No matter what new school he attended, his favorite subjects remained the same. “The idea of using math and physics to build something tangible always clicked with me,” says Nisser. “As a kid, I had always wanted to be an inventor.”
By the time he completed his undergraduate degree, Nisser knew what he aspired to invent. His senior capstone project had drawn upon multiple disciplines and provided the perfect introduction to robotics. “We had to sift through all of the different things we learned in college and combine them to do something interesting. Multidisciplinarity is often essential in robotics and part of what makes it so alluring to me,” he says.
Designing robots prepared for space
After discovering his love for robotics, Nisser enrolled in a master’s program in robotics, systems, and control at ETH Zurich, during which time he met a Harvard professor who directed the Harvard Microrobotics Laboratory and invited Nisser to write his thesis there. His thesis involved building robots that could fold to assemble themselves. “We used layers of materials including shape memory polymers, which are smart materials that can be programmed to changed their shape under different temperature conditions,” says Nisser. “This allowed us to program 2D multilayer sheets to fold in particular ways in order to acquire targeted 3D configurations.”
The experience brought Nisser to his current interest in exporing how robots can be automatically fabricated using both top-down processes like 3D printing and bottom-up processes like self-assembly. He notes that this engineering goal opens a wide door of academic questions. “The multidisciplinarity required to build these engineering systems — from mechanical and electrical engineering to computer science — means you’re always learning something new. Every once in a while, you get to apply a technique you’ve learned in one discipline to another, in a way it hasn’t been used before,” he says. “That’s usually when something interesting happens.”
Prior to beginning his PhD, Nisser also researched reconfigurable robots at the European Space Agency. This project helped him realize he could combine his passion for robotics with his interest in space. “Because every system launched into space has to fit within the confines of a rocket firing, space agencies are interested in structures that can self-reconfigure between smaller and larger shapes,” he says. “I saw a great opportunity to build on what I’d learned about self-folding robotics. I developed algorithms that would allow large numbers of spacecraft modules to move together, attach to one another, and then reconfigure together into a target shape.”
Now a PhD student in the HCI Engineering Group at MIT’s Computer Science and Artificial Intelligence Laboratory, Nisser has partnered with the MIT Space Exploration Initiative to continue studying self-assembly in space. His team is developing a new kind of 3D printing technique adapted to the space environment, allowing them to create novel structures without the constraints of gravity. He recently tested his work on a parabolic flight, which allowed him to experience weightlessness for several intervals of 20 seconds. This December, the project will be launched to the International Space Station with SpaceX for a 30-day science mission.
Making hardware more accessible
To Nisser, studying self-configuration and self-assembly is also key to addressing important social issues. He is particularly interested in how his research can improve sustainability and make advanced technology more affordable. “We typically build systems to perform a specific task, like a chair or a car. However the long-term vision is to be able to create systems from modular, smart components that let the system reconfigure and adjust its functionality to diverse needs,” Nisser says. “By addressing core challenges along the way, we aim to develop technology for the short term too.”
Nisser has already begun to address this challenge by constructing LaserFactory, an add-on device for only $150 that connects to laser cutters and produces custom-designed devices ranging from electronic wearables to functional drones. The fabrication process requires no further instructions to operate — finished drones can fly straight off the assembly line. The device has already been featured by the BBC and other outlets for its ingenuity. “The ability to print fully functional robots is also important for space, where creating on-demand electromechanical devices without any human intervention is paramount to enabling long-duration missions,” he adds.
In his free time, Nisser furthers his goal of democratizing technology by teaching introductory programming to incarcerated women. His lessons are through Brave Behind Bars, a program he and grad student Marisa Gaetz created last year after learning about the U.S. mass incarceration rate. “Almost one in a hundred people in the U.S. today are incarcerated, and more than 80 percent of those will return to prison within a few years of release” he says. “Providing incarcerated people with educational opportunities that promote success in today’s digital world is one of the most effective ways to help reduce this recidivism.”
After graduating, Nisser hopes to continue teaching and conducting robotics research by pursuing a career as a professor. He looks forward to doing more projects related to space and hardware accessibility. “The closer we get toward automating assembly, the sooner we can reduce costs and increase accessibility to all kinds of advanced hardware systems,” says Nisser.
“Initiatives like One Laptop Per Child helped increase awareness of the tremendous benefits of connecting people to the internet by letting people share and create things digitally. The same analogy translates to hardware,” he says. “By distributing fabrication via inexpensive printers or self-assembling hardware that remove the need for engineering expertise, we create an opportunity for people to share and create things physically. And that’s good for everyone.”
With the addition of computers, laser cutters have rapidly become a relatively simple and powerful tool, with software controlling shiny machinery that can chop metals, woods, papers, and plastics. While this curious amalgam of materials feels encompassing, users still face difficulties distinguishing between stockpiles of visually similar materials, where the wrong stuff can make gooey messes, give off horrendous odors, or worse, spew out harmful chemicals.
Addressing what might not be totally apparent to the naked eye, scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) came up with “SensiCut,” a smart material-sensing platform for laser cutters. In contrast to conventional, camera-based approaches that can easily misidentify materials, SensiCut uses a more nuanced fusion. It identifies materials using deep learning and an optical method called “speckle sensing,” a technique that uses a laser to sense a surface’s microstructure, enabled by just one image-sensing add-on.
A little assistance from SensiCut could go a long way — it could potentially protect users from hazardous waste, provide material-specific knowledge, suggest subtle cutting adjustments for better results, and even engrave various items like garments or phone cases that consist of multiple materials.
“By augmenting standard laser cutters with lensless image sensors, we can easily identify visually similar materials commonly found in workshops and reduce overall waste,” says Mustafa Doga Dogan, PhD candidate at MIT CSAIL. “We do this by leveraging a material’s micron-level surface structure, which is a unique characteristic even when visually similar to another type. Without that, you’d likely have to make an educated guess on the correct material name from a large database.”
Beyond using cameras, sticker tags (like QR codes) have also been used on individual sheets to identify them. Which seems straightforward, however, during laser cutting, if the code is cut off from the main sheet, it can’t be identified for future uses. Also, if an incorrect tag is attached, the laser cutter will assume the wrong material type.
To successfully play a round of “what material is this,” the team trained SensiCut’s deep neural network on images of 30 different material types of over 38,000 images, where it could then differentiate between things like acrylic, foamboard, and styrene, and even provide further guidance on power and speed settings.
In one experiment, the team decided to build a face shield, which would require distinguishing between transparent materials from a workshop. The user would first select a design file in the interface, and then use the “pinpoint” function to get the laser moving to identify the material type at a point on the sheet. The laser interacts with the very tiny features of the surface and the rays are reflected off it, arriving at the pixels of the image sensor and producing a unique 2-D image. The system could then alert or flag the user that their sheet is polycarbonate, which means potentially highly toxic flames if cut by a laser.
The speckle imaging technique was used inside a laser cutter, with low-cost, off-the shelf-components, like a Raspberry Pi Zero microprocessor board. To make it compact, the team designed and 3-D printed a lightweight mechanical housing.
Beyond laser cutters, the team envisions a future where SensiCut’s sensing technology could eventually be integrated into other fabrication tools like 3-D printers. To capture additional nuances, they also plan to extend the system by adding thickness detection, a pertinent variable in material makeup.
Dogan wrote the paper alongside undergraduate researchers Steven Acevedo Colon and Varnika Sinha in MIT's Department of Electrical Engineering and Computer Science, Associate Professor Kaan Akşit of University College London, and MIT Professor Stefanie Mueller.
The team will present their work at the ACM Symposium on User Interface Software and Technology (UIST) in October. The work was supported by the NSF Award 1716413, the MIT Portugal Initiative, and the MIT Mechanical Engineering MathWorks Seed Fund Program.
The following press release was issued today by the Broad Institute of MIT and Harvard.
Researchers from MIT, the McGovern Institute for Brain Research at MIT, the Howard Hughes Medical Institute, and the Broad Institute of MIT and Harvard have developed a new way to deliver molecular therapies to cells. The system, called SEND, can be programmed to encapsulate and deliver different RNA cargoes. SEND harnesses natural proteins in the body that form virus-like particles and bind RNA, and it may provoke less of an immune response than other delivery approaches.
The new delivery platform works efficiently in cell models, and, with further development, could open up a new class of delivery methods for a wide range of molecular medicines — including those for gene editing and gene replacement. Existing delivery vehicles for these therapeutics can be inefficient and randomly integrate into the genome of cells, and some can stimulate unwanted immune reactions. SEND has the promise to overcome these limitations, which could open up new opportunities to deploy molecular medicine.
“The biomedical community has been developing powerful molecular therapeutics, but delivering them to cells in a precise and efficient way is challenging,” said CRISPR pioneer Feng Zhang, senior author on the study, core institute member at the Broad Institute, investigator at the McGovern Institute, and the James and Patricia Poitras Professor of Neuroscience at MIT. “SEND has the potential to overcome these challenges.” Zhang is also an investigator at the Howard Hughes Medical Institute and a professor in MIT’s Departments of Brain and Cognitive Sciences and Biological Engineering.
Reporting in Science, the team describes how SEND (Selective Endogenous eNcapsidation for cellular Delivery) takes advantage of molecules made by human cells. At the center of SEND is a protein called PEG10, which normally binds to its own mRNA and forms a spherical protective capsule around it. In their study, the team engineered PEG10 to selectively package and deliver other RNA. The scientists used SEND to deliver the CRISPR-Cas9 gene editing system to mouse and human cells to edit targeted genes.
First author Michael Segel, a postdoctoral researcher in Zhang’s lab, and Blake Lash, second author and a graduate student in the lab, said PEG10 is not unique in its ability to transfer RNA. “That's what’s so exciting,” said Segel. “This study shows that there are probably other RNA transfer systems in the human body that can also be harnessed for therapeutic purposes. It also raises some really fascinating questions about what the natural roles of these proteins might be.”
Inspiration from within
The PEG10 protein exists naturally in humans and is derived from a “retrotransposon” — a virus-like genetic element — that integrated itself into the genome of human ancestors millions of years ago. Over time, PEG10 has been co-opted by the body to become part of the repertoire of proteins important for life.
Four years ago, researchers showed that another retrotransposon-derived protein, ARC, forms virus-like structures and is involved in transferring RNA between cells. Although these studies suggested that it might be possible to engineer retrotransposon proteins as a delivery platform, scientists had not successfully harnessed these proteins to package and deliver specific RNA cargoes in mammalian cells.
Knowing that some retrotransposon-derived proteins are able to bind and package molecular cargo, Zhang’s team turned to these proteins as possible delivery vehicles. They systematically searched through these proteins in the human genome for ones that could form protective capsules. In their initial analysis, the team found 48 human genes encoding proteins that might have that ability. Of these, 19 candidate proteins were present in both mice and humans. In the cell line the team studied, PEG10 stood out as an efficient shuttle; the cells released significantly more PEG10 particles than any other protein tested. The PEG10 particles also mostly contained their own mRNA, suggesting that PEG10 might be able to package specific RNA molecules.
Developing a modular system
To develop the SEND technology, the team identified the molecular sequences, or “signals,” in PEG10’s mRNA that PEG10 recognizes and uses to package its mRNA. The researchers then used these signals to engineer both PEG10 and other RNA cargo so that PEG10 could selectively package those RNAs. Next, the team decorated the PEG10 capsules with additional proteins, called “fusogens,” that are found on the surface of cells and help them fuse together.
By engineering the fusogens on the PEG10 capsules, researchers should be able to target the capsule to a particular kind of cell, tissue, or organ. As a first step towards this goal, the team used two different fusogens, including one found in the human body, to enable delivery of SEND cargo.
“By mixing and matching different components in the SEND system, we believe that it will provide a modular platform for developing therapeutics for different diseases,” said Zhang.
Advancing gene therapy
SEND is composed of proteins that are produced naturally in the body, which means it may not trigger an immune response. If this is demonstrated in further studies, the researchers say SEND could open up opportunities to deliver gene therapies repeatedly with minimal side effects. “The SEND technology will complement viral delivery vectors and lipid nanoparticles to further expand the toolbox of ways to deliver gene and editing therapies to cells,” said Lash.
Next, the team will test SEND in animals and further engineer the system to deliver cargo to a variety of tissues and cells. They will also continue to probe the natural diversity of these systems in the human body to identify other components that can be added to the SEND platform.
“We’re excited to keep pushing this approach forward,” said Zhang. “The realization that we can use PEG10, and most likely other proteins, to engineer a delivery pathway in the human body to package and deliver new RNA and other potential therapies is a really powerful concept.”
This work was made possible with support from the Simons Center for the Social Brain at MIT; National Institutes of Health Intramural Research Program; National Institutes of Health grants 1R01-HG009761 and 1DP1-HL141201; Howard Hughes Medical Institute; Open Philanthropy; G. Harold and Leila Y. Mathers Charitable Foundation; Edward Mallinckrodt, Jr. Foundation; Poitras Center for Psychiatric Disorders Research at MIT; Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT; Yang-Tan Center for Molecular Therapeutics at MIT; Lisa Yang; Phillips family; R. Metcalfe; and J. and P. Poitras.