A Greek veto prevents the EU from reendorsing a global carbon price on shipping in its position for next month’s climate summit.

The Department of Homeland Security says the Biden administration noted the presence of placards supporting Donald Trump 100 times after Hurricane Helene hit North Carolina in 2024.

An international tracking effort is gaining steam, as more fossil fuel companies agree to take field measurements of their emissions.

The joint venture seeks to challenge a rapid expansion of Chinese automakers in Central and South America.

The European Commission is reviewing rules designed to accelerate the automotive sector’s green transition.

The surprise decision follows a string of unexpected changes to the EU’s main tool to end deforestation.

Users will be able to track unusual temperatures, heavy rainfall, as well as drought periods going back as far as January 1981.

“Deepening and integrating EU capital markets is critical to support the large-scale investments we need," Christine Lagarde said.

Nature Climate Change, Published online: 22 October 2025; doi:10.1038/s41558-025-02469-w

Heatwaves worsen educational inequality in Brazil

Nature Climate Change, Published online: 22 October 2025; doi:10.1038/s41558-025-02459-y

Emissions reductions of rooftop solar are overstated by approaches that inadequately capture substitution effects

The degree to which someone trusts the information depicted in a chart can depend on their assumptions about who made the data visualization, according to a pair of studies by MIT researchers.

For instance, if someone infers that a graph about a controversial topic like gun violence was produced by an organization they feel is in opposition with their beliefs or political views, they may discredit the information or dismiss the visualization all together.

The researchers found that even the clearest visualizations often communicate more than the data they explicitly depict, and can elicit strong judgments from viewers about the social contexts, identities, and characteristics of those who made the chart.

Readers make these assessments about the social context of a visualization primarily from its design features, like the color palette or the way information is arranged, rather than the underlying data. Often, these inferences are unintended by the designers.

Qualitative and quantitative studies revealed that these social inferences aren’t restricted to certain subgroups, nor are they caused by limited data literacy.

The researchers consolidate their findings into a framework that scientists and communicators can use to think critically about how design choices might affect these social assumptions. Ultimately, they hope this work leads to better strategies for scientific communication.

“If you are scrolling through social media and you see a chart, and you immediately dismiss it as something an influencer has produced just to get attention, that shapes your entire experience with the chart before you even dig into the data. We’ve shown in these papers that visualizations do more than just communicate the data they are depicting — they also communicate other social signals,” says Arvind Satyanarayan, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS) and member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and co-senior author of this research.

He is joined on the paper by co-lead authors Amy Rae Fox, a former CSAIL postdoc, and Michelle Morgenstern, a current postdoc in MIT’s anthropology program; and co-senior author Graham M. Jones, professor of anthropology. Two related papers on this research will be presented at the IEEE Visualization Conference.

Charts as social artifacts

During the height of the Covid-19 pandemic, social media was awash in charts from organizations like the World Health Organization and Centers for Disease Control and Prevention, which were designed to convey information about the spread of disease.

The MIT researchers studied how these visualizations were being used to discuss the pandemic. They found that some citizen scientists were using the underlying data to make visualizations of their own, challenging the findings of mainstream science.

“This was an unexpected discovery as, previously, citizen scientists were typically aligned with mainstream scientists. It took us a few years to figure out how to study this phenomenon more deeply,” Satyanarayan says.

Most research into data visualization studies how charts communicate data. Instead, the researchers wanted to explore visualizations from a social and linguistic perspective to assess the information they convey beyond the data.

Linguistic anthropologists have found that, while language allows people to communicate ideas, it also holds social meaning beyond the words people use. For instance, an accent or dialect can indicate that someone is part of a particular community.

By “pointing” to certain social meanings, identities, and characteristics, language serves what is known as a socio-indexical function.

“We wanted to see if things in the visual language of data communication might point to certain institutions, or the kinds of people in those institutions, that carry a meaning that could be unintended by the makers of the visualization,” Jones says.

To do this, the researchers conducted an initial, qualitative study of users on the social media platform Tumblr. During one-on-one interviews, the researchers showed users a variety of real visualizations from online sources, as well as modified visualizations where they removed the textual information, like titles and axes labels.

Stripping out the textual information was particularly important, since it mimics the way people often interact with online visualizations.

“Our engagement with social media is a few quick seconds. People aren’t taking the time to read the title of a chart or look at the data very carefully,” Satyanarayan says.

The interviews revealed that users made detailed inferences about the people or organizations who created the visualizations based on what they called “vibes,” design elements, like colors or the use of certain graphics. These inferences in turn impacted their trust in the data.

For instance, after seeing a chart with the flags of Georgia and Texas and a graph with two lines in red and black, but no text, one user said, “This kind of looks like something a Texas Republican (legislator) would put on Twitter or on their website, or as part of a campaign presentation.”

A quantitative approach

Building on this initial work, the researchers used the same methodology in three quantitative studies involving surveys sent to larger groups of people from a variety of backgrounds.

They found the same phenomenon: People make inferences about the social context of a visualization based on its design, which can lead to misunderstandings about, and mistrust in, the data it depicts.

For instance, users felt some visualizations were so neatly arranged they believed them to be advertisements, and therefore not trustworthy. In another example, one user dismissed a chart by a Pulitzer-prize winning designer because they felt the hand-drawn graphical style indicated it was made by “some female Instagram influencer who is just trying to look for attention.”

“If that is the first reaction someone has to a chart, it is going to massively impact the degree to which they trust it,” Satyanarayan says.

Moreover, when the researchers reintroduced text in the visualizations from which it had been removed, users still made these social inferences.

Typically, in data visualization, the solution to such a problem would be to create clearer charts or educate people about data literacy. But this research points to a completely different kind of data literacy, Jones says.

“It is not erroneous for people to be drawing these inferences. It requires a lot of cultural knowledge about where visualizations come from, how they are made, and how they circulate. Drawing these inferences is a feature, not a bug, of the way we use signs,” he says.

From these results, they created a classification framework to organize the social inferences users made and the design elements that contributed to them. They hope the typology serves as a tool designers can use to develop more effective visualizations, as well as a starting point for additional studies.

Moving forward, the researchers want to continue exploring the role of data visualizations as social artifacts, perhaps by drilling down on each design feature they identified in the typology. They also want to expand the scope of their study to include visualizations in research papers and scientific journals.

“Part of the value of this work is a methodological contribution to render a set of phenomena amenable to experimental study. But this work is also important because it showcases an interdisciplinary cross-pollination that is powerful and unique to MIT,” Jones says.

This work was supported, in part, by MIT METEOR and PFPFEE fellowships, an Amar G. Bose Fellowship, an Alfred P. Sloan Fellowship, and the National Science Foundation.

Coming from a small high school in rural South Dakota that didn’t offer advanced placement (AP) classes, Titus Roesler ’25 didn’t have the easiest start at MIT. But when his efforts to catch up academically to his peers led to a job as a teaching assistant, it changed everything.

Roesler, who graduated last spring with a bachelor’s degree in electrical engineering and is now working on a master’s, has built a reputation for himself as a student-teacher at MIT. Since discovering his affinity for teaching and mentoring, he’s been a teaching assistant for four different classes and designed two seminars from scratch.

Through teaching, Roesler has not only helped other students, but also improved his own grasp of complex subjects. That includes signal processing, which involves manipulating signals, such as radio waves, to make them more useful for applications like wireless communications. He has become fascinated by the topic and hopes to continue working in the field.

Roesler lights up when talking about teaching, but he didn’t always think it was in the cards.

“I don't know that anyone who knew me pre-MIT would believe that I do things like give recitations to crowded rooms, because I think everyone thought, ‘Titus is that quiet kid, he never talked at all.’”

Learning through teaching

Growing up in Marion, South Dakota, a town with a population around 800, Roesler didn’t have MIT on his radar, but he knew he liked math. His high school capstone project involved helping his classmates on the math section of the ACT, and he tutored a few of his classmates. His teacher let him teach trigonometry one day, and he toured local colleges with the plan of becoming a high school math teacher.

But that changed after he self-studied calculus through MIT’s OpenCourseWare offerings and set his sights on the Institute.

Roesler worked overtime during his first year at MIT to catch up with what his peers had learned back in high school. On his first physics exam, he answered only one question correctly — a multiple-choice question he had guessed on. But MIT’s Experimental Study Group (ESG) kept him afloat during his first year, and it quickly led to more opportunities.

When, in the spring of his first year, his multivariable calculus instructor asked him to stay after class one day, Roesler was sure he was in trouble. She actually wanted to see if he could TA for her next year.

“I was flattered because there was still a month left in the class. Plenty of time for me to fail,” Roesler jokes.

He loved the job. During a Friday night office hour session, he stayed for extra hours to help a student whom he saw a lot of himself in — someone who was also from a rural background and had also entered MIT without a strong mathematics background. He went on to become the student’s tutor. The position gave him the opportunity to be the teacher he’d always wanted to have.

As a TA, “I wasn't coming at things from the perspective of ‘Everyone already knows A, B, C’ before I explained. I would always try to start from the ground up and give my perspective on it,” Roesler says.

From his mentorship and teaching work, he received the Undergraduate Teaching Award from the Department of Electrical Engineering and Computer Science and the Outstanding Associate Advisor Award from the Office of the First Year. After joining ESG during his first year, Roesler stayed on as an associate advisor in the learning community for the next three years. His work earned him the Fiekowsky Award for Excellence in Teaching and the Fiekowsky Award for Community Service.

The right blend

Signal processing, the focus of his graduate work, “is where calculus, geometry, linear algebra, probability, statistics, algorithms, and numerical analysis all come into play on practical problems of real-world interest,” Roesler says. “For me, it’s the right blend of theory and application.”

Due to the field’s wide scope, Roesler notices potential applications for signal processing everywhere, and how different fields intersect within the discipline. “Everything comes together in just the right way,” he says.

He is especially interested in signal-processing problems such as source separation, which aims to recover a set of source signals from a set of mixed signals. During his senior year, he spent two semesters on a project where he wrote a Python program to separate harmonies in Bach chorales.

For his master’s degree, following a summer research internship at MIT Lincoln Laboratory, Roesler has stayed at the laboratory, this time venturing into high-frequency radio communications. He’s currently working on a research project that applies the theory of compressed sensing (which states that, under certain conditions, it is possible to reconstruct signals from very few measurements) to communications.

What fascinates Roesler are “something-from-nothing” problems.

“The kind of problems I’m interested in are underdetermined, inverse problems,” he says. For example, imagine trying to reconstruct a full image from only a handful of pixels. While on the surface this seems impossible, researchers have recovered quality images by applying the techniques of compressed sensing.

Running and serving

Roesler has also spent extensive time running, a sport he’s loved since fifth grade. In 2023, he raced a marathon in 2 hours and 46 minutes and went on to run the Boston Marathon in both 2024 and 2025. To prepare, he spent a lot of time reading up on the psychology of running, which he says was the first time he used the scientific method. Now, he just runs for fun and uses it as a way to focus and collect this thoughts.

He has also served on the executive team of the Undergraduate Mathematics Association, as a resident peer mentor at Baker House, and a tutor for two classes. At the PKG Center, he’s been a program lead and counselor for its pre-orientation program.

Roesler still gets excited about seeing the impact of his teaching. At the end of one semester teaching a tutorial, he took his class on a picnic. They surprised him with a card and a bag of goodies. 

Recalling the moment, he says: “I thought, How does it get better? It was wonderful.”

Nervous system functions, from motion to perception to cognition, depend on the active zones of neural circuit connections, or “synapses,” sending out the right amount of their chemical signals at the right times. By tracking how synaptic active zones form and mature in fruit flies, researchers at The Picower Institute for Learning and Memory at MIT have revealed a fundamental model for how neural activity during development builds properly working connections.

Understanding how that happens is important, not only for advancing fundamental knowledge about how nervous systems develop, but also because many disorders such as epilepsy, autism, or intellectual disability can arise from aberrations of synaptic transmission, says senior author Troy Littleton, the Menicon Professor in The Picower Institute and MIT’s Department of Biology. The new findings, funded in part by a 2021 grant from the National Institutes of Health, provide insights into how active zones develop the ability to send neurotransmitters across synapses to their circuit targets. It’s not instant or predestined, the study shows. It can take days to fully mature, and that is regulated by neural activity.

If scientists can fully understand the process, Littleton says, then they can develop molecular strategies to intervene to tweak synaptic transmission when it’s happening too much or too little in disease.

“We’d like to have the levers to push to make synapses stronger or weaker, that’s for sure,” Littleton says. “And so knowing the full range of levers we can tug on to potentially change output would be exciting.”

Littleton Lab research scientist Yuliya Akbergenova led the study published Oct. 14 in the Journal of Neuroscience.

How newborn synapses grow up

In the study, the researchers examined neurons that send the neurotransmitter glutamate across synapses to control muscles in the fly larvae. To study how the active zones in the animals matured, the scientists needed to keep track of their age. That hasn’t been possible before, but Akbergenova overcame the barrier by cleverly engineering the fluorescent protein mMaple, which changes its glow from green to red when zapped with 15 seconds of ultraviolet light, into a component of the glutamate receptors on the receiving side of the synapse. Then, whenever she wanted, she could shine light and all the synapses already formed before that time would glow red, and any new ones that formed subsequently would glow green.

With the ability to track each active zone’s birthday, the authors could then document how active zones developed their ability to increase output over the course of days after birth. The researchers actually watched as synapses were built over many hours by tagging each of eight kinds of proteins that make up an active zone. At first, the active zones couldn’t transmit anything. Then, as some essential early proteins accumulated, they could send out glutamate spontaneously, but not if evoked by electrical stimulation of their host neuron (simulating how that neuron might be signaled naturally in a circuit). Only after several more proteins arrived did active zones possess the mature structure for calcium ions to trigger the fusion of glutamate vesicles to the cell membrane for evoked release across the synapse.

Activity matters

Of course, construction does not go on forever. At some point, the fly larva stops building one synapse and then builds new ones further down the line as the neuronal axon expands to keep up with growing muscles. The researchers wondered whether neural activity had a role in driving that process of finishing up one active zone and moving on to build the next.

To find out, they employed two different interventions to block active zones from being able to release glutamate, thereby preventing synaptic activity. Notably, one of the methods they chose was blocking the action of a protein called Synaptotagmin 1. That’s important because mutations that disrupt the protein in humans are associated with severe intellectual disability and autism. Moreover, the researchers tailored the activity-blocking interventions to just one neuron in each larva because blocking activity in all their neurons would have proved lethal.

In neurons where the researchers blocked activity, they observed two consequences: the neurons stopped building new active zones and instead kept making existing active zones larger and larger. It was as if the neuron could tell the active zone wasn’t releasing glutamate and tried to make it work by giving it more protein material to work with. That effort came at the expense of starting construction on new active zones.

“I think that what it’s trying to do is compensate for the loss of activity,” Littleton says.

Testing indicated that the enlarged active zones the neurons built in hopes of restarting activity were functional (or would have been if the researchers weren’t artificially blocking them). This suggested that the way the neuron sensed that glutamate wasn’t being released was therefore likely to be a feedback signal from the muscle side of the synapse. To test that, the scientists knocked out a glutamate receptor component in the muscle, and when they did, they found that the neurons no longer made their active zones larger.

Littleton says the lab is already looking into the new questions the discoveries raise. In particular: What are the molecular pathways that initiate synapse formation in the first place, and what are the signals that tell an active zone it has finished growing? Finding those answers will bring researchers closer to understanding how to intervene when synaptic active zones aren’t developing properly.

In addition to Littleton and Akbergenova, the paper’s other authors are Jessica Matthias and Sofya Makeyeva.

In addition to the National Institutes of Health, The Freedom Together Foundation provided funding for the study.

When it comes to artificial intelligence, MIT and IBM were there at the beginning: laying foundational work and creating some of the first programs — AI predecessors — and theorizing how machine “intelligence” might come to be.

Today, collaborations like the MIT-IBM Watson AI Lab, which launched eight years ago, are continuing to deliver expertise for the promise of tomorrow’s AI technology. This is critical for industries and the labor force that stand to benefit, particularly in the short term: from $3-4 trillion of forecast global economic benefits and 80 percent productivity gains for knowledge workers and creative tasks, to significant incorporations of generative AI into business processes (80 percent) and software applications (70 percent) in the next three years.

While industry has seen a boom in notable models, chiefly in the past year, academia continues to drive the innovation, contributing most of the highly cited research. At the MIT-IBM Watson AI Lab, success takes the form of 54 patent disclosures, an excess of 128,000 citations with an h-index of 162, and more than 50 industry-driven use cases. Some of the lab’s many achievements include improved stent placement with AI imaging techniques, slashing computational overhead, shrinking models while maintaining performance, and modeling of interatomic potential for silicate chemistry.

“The lab is uniquely positioned to identify the ‘right’ problems to solve, setting us apart from other entities,” says Aude Oliva, lab MIT director and director of strategic industry engagement in the MIT Schwarzman College of Computing. “Further, the experience our students gain from working on these challenges for enterprise AI translates to their competitiveness in the job market and the promotion of a competitive industry.”

“The MIT-IBM Watson AI Lab has had tremendous impact by bringing together a rich set of collaborations between IBM and MIT’s researchers and students,” says Provost Anantha Chandrakasan, who is the lab’s MIT co-chair and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “By supporting cross-cutting research at the intersection of AI and many other disciplines, the lab is advancing foundational work and accelerating the development of transformative solutions for our nation and the world.”

Long-horizon work

As AI continues to garner interest, many organizations struggle to channel the technology into meaningful outcomes. A 2024 Gartner study finds that, “at least 30% of generative AI projects will be abandoned after proof of concept by the end of 2025,” demonstrating ambition and widespread hunger for AI, but a lack of knowledge for how to develop and apply it to create immediate value.

Here, the lab shines, bridging research and deployment. The majority of the lab’s current-year research portfolio is aligned to use and develop new features, capacities, or products for IBM, the lab’s corporate members, or real-world applications. The last of these comprise large language models, AI hardware, and foundation models, including multi-modal, bio-medical, and geo-spatial ones. Inquiry-driven students and interns are invaluable in this pursuit, offering enthusiasm and new perspectives while accumulating domain knowledge to help derive and engineer advancements in the field, as well as opening up new frontiers for exploration with AI as a tool.

Findings from the AAAI 2025 Presidential panel on the Future of AI Research support the need for contributions from academia-industry collaborations like the lab in the AI arena: “Academics have a role to play in providing independent advice and interpretations of these results [from industry] and their consequences. The private sector focuses more on the short term, and universities and society more on a longer-term perspective.”

Bringing these strengths together, along with the push for open sourcing and open science, can spark innovation that neither could achieve alone. History shows that embracing these principles, and sharing code and making research accessible, has long-term benefits for both the sector and society. In line with IBM and MIT’s missions, the lab contributes technologies, findings, governance, and standards to the public sphere through this collaboration, thereby enhancing transparency, accelerating reproducibility, and ensuring trustworthy advances.

The lab was created to merge MIT’s deep research expertise with IBM’s industrial R&D capacity, aiming for breakthroughs in core AI methods and hardware, as well as new applications in areas like health care, chemistry, finance, cybersecurity, and robust planning and decision-making for business.

Bigger isn't always better

Today, large foundation models are giving way to smaller, more task-specific models yielding better performance. Contributions from lab members like Song Han, associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), and IBM Research’s Chuang Gan help make this possible, through work such as once-for-all and AWQ. Innovations such as these improve efficiency with better architectures, algorithm shrinking, and activation-aware weight quantization, letting models like language processing run on edge devices at faster speeds and reduced latency.

Consequently, foundation, vision, multimodal, and large language models have seen benefits, allowing for the lab research groups of Oliva, MIT EECS Associate Professor Yoon Kim, and IBM Research members Rameswar Panda, Yang Zhang, and Rogerio Feris to build on the work. This includes techniques to imbue models with external knowledge and the development of linear attention transformer methods for higher throughput, compared to other state-of-the-art systems. 

Understanding and reasoning in vision and multimodal systems has also seen a boon. Works like “Task2Sim” and “AdaFuse” demonstrate improved vision model performance if pre-training takes place on synthetic data, and how video action recognition can be boosted by fusing channels from past and current feature maps.

As part of a commitment to leaner AI, the lab teams of Gregory Wornell, the MIT EECS Sumitomo Electric Industries Professor in Engineering, IBM Research’s Chuang Gan, and David Cox, VP for foundational AI at IBM Research and the lab’s IBM director, have shown that model adaptability and data efficiency can go hand in hand. Two approaches, EvoScale and Chain-of-Action-Thought reasoning (COAT), enable language models to make the most of limited data and computation by improving on prior generation attempts through structured iteration, narrowing in on a better response. COAT uses a meta-action framework and reinforcement learning to tackle reasoning-intensive tasks via self-correction, while EvoScale brings a similar philosophy to code generation, evolving high-quality candidate solutions. These techniques help to enable resource-conscious, targeted, real-world deployment.

“The impact of MIT-IBM research on our large language model development efforts cannot be overstated,” says Cox. “We’re seeing that smaller, more specialized models and tools are having an outsized impact, especially when they are combined. Innovations from the MIT-IBM Watson AI Lab help shape these technical directions and influence the strategy we are taking in the market through platforms like watsonx.”

For example, numerous lab projects have contributed features, capabilities, and uses to IBM’s Granite Vision, which provides impressive computer vision designed for document understanding, despite its compact size. This comes at a time when there’s a growing need for extraction, interpretation, and trustworthy summarization of information and data contained in long formats for enterprise purposes.

Other achievements that extend beyond direct research on AI and across disciplines are not only beneficial, but necessary for advancing the technology and lifting up society, concludes the 2025 AAAI panel.

Work from the lab’s Caroline Uhler and Devavrat Shah — both Andrew (1956) and Erna Viterbi Professors in EECS and the Institute for Data, Systems, and Society (IDSS) — along with IBM Research’s Kristjan Greenewald, transcends specializations. They are developing causal discovery methods to uncover how interventions affect outcomes, and identify which ones achieve desired results. The studies include developing a framework that can both elucidate how “treatments” for different sub-populations may play out, like on an ecommerce platform or mobility restrictions on morbidity outcomes. Findings from this body of work could influence the fields of marketing and medicine to education and risk management.

“Advances in AI and other areas of computing are influencing how people formulate and tackle challenges in nearly every discipline. At the MIT-IBM Watson AI Lab, researchers recognize this cross-cutting nature of their work and its impact, interrogating problems from multiple viewpoints and bringing real-world problems from industry, in order to develop novel solutions,” says Dan Huttenlocher, MIT lab co-chair, dean of the MIT Schwarzman College of Computing, and the Henry Ellis Warren (1894) Professor of Electrical Engineering and Computer Science.

A significant piece of what makes this research ecosystem thrive is the steady influx of student talent and their contributions through MIT’s Undergraduate Research Opportunities Program (UROP), MIT EECS 6A Program, and the new MIT-IBM Watson AI Lab Internship Program. Altogether, more than 70 young researchers have not only accelerated their technical skill development, but, through guidance and support by the lab’s mentors, gained knowledge in AI domains to become emerging practitioners themselves. This is why the lab continually seeks to identify promising students at all stages in their exploration of AI’s potential.

“In order to unlock the full economic and societal potential of AI, we need to foster ‘useful and efficient intelligence,’” says Sriram Raghavan, IBM Research VP for AI and IBM chair of the lab. “To translate AI promise into progress, it’s crucial that we continue to focus on innovations to develop efficient, optimized, and fit-for-purpose models that can easily be adapted to specific domains and use cases. Academic-industry collaborations, such as the MIT-IBM Watson AI Lab, help drive the breakthroughs that make this possible.”

Recently, more than 1,000 MIT students stepped into the shoes of global decision-makers by trying out En-ROADS, a simulation tool developed to test climate policies, explore solutions, and envision a cleaner and safer environmental future.

MIT is committed to climate action, and this year’s new student orientation showcased that commitment. For the first time ever, incoming Leaders for Global Operations (LGO), Executive MBA, Sloan Fellow MBA, MBA, and undergraduate students all explored the capabilities of En-ROADS.

“The goal is for MIT to become one of the world’s most prolific, collaborative, and interdisciplinary sources of technological, behavioral, and policy solutions for the global climate challenge over the next decade,” MIT Provost Anantha P. Chandrakasan told an audience of about 300 undergraduates from the Class of 2029. “It is something we need to do urgently, and today is your opportunity to play a role in that bold mission.”

Connecting passion with science for change

In group workshop sessions, students collaborated to create a world in which global warming stays well below 2 degrees Celsius above preindustrial levels — the goal of the 2015 Paris Agreement. Backed by the latest science, the En-ROADS simulator let them explore firsthand how policies like carbon pricing and clean energy investments affect our climate, economy, and health. Over 450 incoming MBA students even role-played as delegates at a global climate summit conference, tasked with negotiating a global agreement to address the harm caused by climate change.

For first-year MBA student Allison Somuk, who played the role of President Xi Jinping of China, the workshop was not only eye-opening about climate, but also altered how she plans to approach her future work and advocacy.

“Before the simulation, I didn’t have data on climate change, so I was surprised to see how close we are to catastrophic temperature increases. What surprised me most was how difficult it was to slow that trajectory. It required significant action and compromise from nearly every sector, not just a few. As someone passionate about improving maternal health care in developing nations, my view of contributing factors has broadened. I now see how maternal health may be affected by a larger system where climate policy decisions directly affect women’s health outcomes.”

MIT Sloan Research Affiliate Andrew Jones, who is also executive director and co-founder of Climate Interactive and co-creator of the En-ROADS tool, presented several sessions during orientation. Looking back on the week, he found the experience personally rewarding.  

“Engaging with hundreds of students, I was inspired by the powerful alignment between their passion for climate action and MIT’s increased commitment to delivering on climate goals. This is a pivotal moment for breakthroughs on our campus.”

Other presenters included Jennifer Graham, MIT Sustainability Initiative senior associate director; Jason Jay, MIT Sustainability Initiative director; Krystal Noiseux, MIT Climate Pathways Project associate director; Bethany Patten, MIT Climate Policy Center executive director; and John Sterman, Jay W. Forrester Professor of Management, professor in the MIT Institute for Data, Systems, and Society, and director of the MIT System Dynamics Group.

Chris Rabe, the MIT Climate Project’s Education Program director, was impressed, but not surprised, by how much students learned so quickly as they worked together to solve the problem with En-ROADS.

“By integrating reflection, emotional dynamics, multi-generational perspectives, group work, and inquiry, the En-ROADS simulation provides an ideal foundation for first-year students to explore the breadth of climate and sustainability opportunities at MIT. In the process, students came to recognize the many levers and multi-solving approaches required to address the complex challenges of climate change.”

Inspiring climate leaders

The En-ROADS workshops were a true team effort, made possible with the help of senior staff at MIT Sloan School of Management and the MBA program office, and members of the MIT Sloan Sustainability Initiative, Climate Pathways Project, Climate Policy Center, the Climate Project, Office of the First Year, and entire undergraduate Orientation team.

“Altogether, over a thousand of the newest members of the MIT community have now had a chance to learn for themselves about the climate crisis,” says Sterman, “and what we can do to create a healthier, safer, more prosperous, and more sustainable world — and how they can get involved to bring that world into being, even as first-year undergrads and MBAs.” 

By the end of the workshops, the students’ spirits were buoyed. They all had successfully found ways to keep global warming to below 2 C.  When asked, “What would you love about being part of this new future you’ve created?,”  a more positive, optimistic word cloud came into view. Answers included:

• breathing cleaner air;
• giving my children a better and safer environment;
• my hometown would not be flooded constantly;
• rich marine life and protection of reefs;
• exciting, new clean industries;
• increased socioeconomic equality; and
• proof that we as a global community can work together to save ourselves. 

First-year MBA student Ruby Eisenbud sums up the sentiment many new MIT students came away with after their workshop.

“Coming to Sloan, one of the questions on my mind was: How can we, as future leaders, make a positive impact related to climate change? While En-ROADS is a simulation, it felt like we experienced, in the smallest way, what it could be like to be a leader navigating the diverging interests of all stakeholders involved in mitigating the impacts of the climate crisis. While the simulation prompted us to face the difficult reality of climate change, it also reinforced my motivation to emphasize climate in my work at Sloan and beyond.”

On any given day, MIT’s famed 825-foot Infinite Corridor serves as a busy, buzzing pedestrian highway, offering campus commuters a quick, if congested, route from point A to B. With the possible exception of MIT Henge twice a year, it doesn’t exactly invite lingering.

Thanks to a recent renovation on the first floor of Building 11, the former location of Student Financial Services, there’s now a compelling reason for students to step off the busy throughfare and pause for conversation or respite.

Dubbed by one onlooker as “the spaceport,” the area has been transformed into an airy, multi-functional hub. Nestled inside is the Undergraduate Advising Center (UAC), which launched in 2023 to provide holistic support for students’ personal and academic growth by providing individualized advising for all four years, offering guidance about and connections to MIT resources, and partnering with faculty and departments to ensure a comprehensive advising experience.

Students can now find another key service conveniently located close by: Career Advising and Professional Development has moved into renovated office suites just down the hall, in Building 7.

“It’s just stunning!” marvels Diep Luu, senior associate dean and director of the UAC. “You can’t help but notice the contrast between the historic architecture and the contemporary design. The space is filled with natural light thanks to the floor-to-ceiling windows, and it makes the environment both energizing and comfortable.”

Designed by Merge Architects, the 5,000 square-foot space opens off the Infinite with several informal public spaces for students and community members. These include a series of soaring, vaulted booths with a variety of tables and seating to support multiple kinds of socialization and/or work, a cozy lounge lined with pi wallpaper (carried out to 10,638 digits after 3.14), and the “social stairs” for informal gatherings and workshops. Beyond that, glass doors lead to the UAC office space, which features open workstations, private advising rooms, and conference rooms with Zoom capability.

“We wanted to incorporate as many different kinds of spaces to accommodate as many different kinds of interactions as we could,” explains Kate Trimble, senior associate dean and chief of staff of the Division of Graduate and Undergraduate Education (GUE), who helped guide the renovation project. “After all, the UAC will support all undergraduate students for their entire four-year MIT journey, through a wide variety of experiences, challenges, and celebrations.”

Homing in on the  “Boardwalk or Park Place of MIT real estate”

The vision for the new district began to percolate in 2022. At the time, GUE (then known as the Office of the Vice Chancellor, or OVC) was focusing on two separate, key priorities: reconfiguring office space in a post-pandemic, flex-work world; and creating a new undergraduate advising center, in accordance with one of the Task Force 2021 recommendations.

A faculty and staff working group gathered information and ideas from offices and programs that had already implemented “flex-space” strategies, such as Human Resources, IS&T, and the MIT Innovation Headquarters. In thinking about an advising center of the size and scope envisioned, Trimble notes, “we quickly zeroed in on the Building 11 space. It’s such a prominent location. Former Vice Chancellor (and current Vice President for Research) Ian A. Waitz referred to it as the “Boardwalk or Park Place of MIT real estate. And if you’re thinking about a center that’s going to serve all undergraduates, you really want it to be convenient and centrally located — and boy, that’s a perfect space.”

As plans were made to relocate Student Financial Services to a new home in Building E17, the renovation team engaged undergraduate students and advising staff in the design process through a series of charrette-style workshops and focus groups. Students shared feedback about spaces on campus where they felt most comfortable, as well as those they disliked. From staff, the team learned which design elements would make the space as functional as possible, allowing for the variety of interactions they typically have with students.

The team selected Merge Architects for the project, Trimble says, because “they understood that we were not looking to build something that was an architectural temple, but rather a functional and fun space that meets the needs of our students and staff. They’ve been creative and responsive partners.” She also credits the MIT Campus Construction group and the Office of Campus Planning for their crucial role in the renovation. “I can’t say enough good things about them. They’ve been superb guides through a long and complicated process.”

A more student-centric Infinite Corridor

Construction wrapped up in late summer, and the UAC held an open house for students on Registration Day, Sept. 3. It buzzed with activity as students admired the space, chatted with UAC staff, took photos, and met the office mascot, Winni, a friendly chocolate Labrador retriever.

“Students have been amazed by the transformation,” says Luu. “We wanted a space that encourages community and collaboration, one that feels alive and dynamic, and the early feedback suggests that’s exactly what’s happening,” Luu explains. “It also gives us a chance to better connect students not only with what the UAC offers, but also with support across the Institute.

“Last year, the UAC offices were behind these two wooden doors in the Infinite Corridor and you had to know that they were there to get to them,” says junior Caleb Mathewos, who has been a UAC orientation leader and captain over the past two years. “The space is very inviting now. I’ve seen people sitting there and working, or just relaxing between classes. I see my friends every now and then, and I’ll stop by and chat with them. Because it’s so much more open, it makes the UAC feel a lot more accessible to students.”

Senior Calvin Macatantan, who’s been involved with the UAC’s First Generation/Low Income Program since his first year and served as an associate advisor and orientation leader, thinks the new space will make it easier for students — especially first years — to find what they need to navigate at MIT. “Before, resources felt scattered across different parts of the Infinite, even though they had similar missions of advising and supporting students. It's nice that there’s a central, welcoming space where those supports connect, and I think that will make a big difference in how students experience MIT.”

The transformation adds significantly to a trend toward creating more student-centric spaces along the Infinite. In the past few years, MIT has added two new study lounges in Building 3, the DEN and the LODGE, and the Department of Materials Science and Engineering built the DMSE Breakerspace in Building 4. This fall, another office suite along the Infinite will be remodeled into a new tutoring hub.

"It’s wonderful to see the UAC space and the whole advising ‘neighborhood,’ if you will, come to fruition,” says Vice Chancellor for Graduate and Undergraduate Education David L. Darmofal. “The need to strengthen undergraduate advising and the opportunity to do so through an Institute advising hub was an outcome of the Task Force 2021 effort, and it’s taken years of thoughtful reflection by many stakeholders to lay the foundation for such a significant sea change in advising. This space is a tangible, visible commitment to putting students first.”

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