Pavements form the backbone of our built environment. In the United States, almost 2.8 million lane-miles, or about 4.6 million lane-kilometers, are paved. They take us to work or school, take goods to their destinations, and much more.

To secure a more sustainable future, we must take a careful look at the long-term performance and environmental impacts of our pavements. Haoran Li, a postdoc at the MIT Concrete Sustainability Hub and the Department of Civil and Environmental Engineering, is deeply invested in studying how to give stakeholders the information and tools they need to make informed pavement decisions with the future in mind. Here, he discusses life-cycle assessments for pavements as well as research from MIT in addressing pavement sustainability.

Q: What is life-cycle assessment, and why does it matter for pavements?

A: Life-cycle assessment (LCA) is a method that helps us holistically assess the environmental impacts of products and systems throughout their life cycle — everything from the impacts of raw materials to construction, use, maintenance, and repair, and finally decommissioning. For pavements, up to 78 percent of the life-cycle impact comes from the use phase, with the majority stemming from vehicle fuel use impacted by pavement characteristics, such as stiffness and smoothness. This phase also includes the sunlight reflected by pavements: Lighter, more reflective pavement bounces heat back into the atmosphere instead of absorbing it, which can help keep nearby buildings and streets cooler. At the same time, there are positive use phase impacts like carbon uptake — the natural process by which cement-based products like concrete roads and infrastructure sequester CO2 [carbon dioxide] from the atmosphere. Due to the sheer area of our pavements, they offer a great potential for the sustainability solution. Unlike many decarbonization solutions, pavements are managed by government agencies and influence the emissions from vehicles and surrounding buildings, allowing for a coordinated push toward sustainability through better materials, designs, and maintenance.

Q: What are the gaps in current pavement life-cycle assessment methods and tools and what has the MIT Concrete Sustainability Hub done to address them so far?

A: A key gap is the complexity of performing pavement LCA. Practitioners should assess both the long-term structural performance and environmental impacts of paving materials, considering the pavements’ interactions with the built environment. Another key gap is the great uncertainty associated with pavement LCA. Since pavements are designed to last for decades, it is necessary to handle the inherent uncertainty through their long-term performance evaluations.

To tackle these challenges, the MIT Concrete Sustainability Hub (CSHub) developed an innovative method and practical tools that address data intensity and uncertainty while offering context-specific and probabilistic LCA strategies. For instance, we demonstrated that it is possible to achieve meaningful results on the environmentally preferred pavement alternatives while reducing data collection efforts by focusing on the most influential and least variable parameters. By targeting key variables that significantly impact the pavement’s life cycle, we can streamline the process and still obtain robust conclusions. Overall, the efforts of the CSHub aim to enhance the accuracy and efficiency of pavement LCAs, making them better aligned with real-world conditions and more manageable in terms of data requirements.

Q: How does the MIT Concrete Sustainability Hub’s new streamlined pavement life-cycle assessment method improve on previous designs?

A: The CSHub recently developed a new framework to streamline both probabilistic and comparative LCAs for pavements. Probabilistic LCA accounts for randomness and variability in data, while comparative LCA allows the analysis of different options simultaneously to determine the most sustainable choice.

One key innovation is the use of a structured data underspecification approach, which prioritizes the data collection efforts. In pavement LCA, underspecifying can reduce the overall data collection burden by up to 85 percent, allowing for a reliable decision-making process with minimal data. By focusing on the most critical elements, we can still reach robust conclusions without the need for extensive data collection.

To make this framework practical and accessible, it is being integrated into an online LCA software tool. This tool facilitates use by practitioners, such as departments of transportation and metropolitan planning organizations. It helps them identify choices that lead to the highest-performing, longest-lasting, and most environmentally friendly pavements. Some of these solutions could include incorporating low-carbon concrete mixtures, prioritizing long-lasting treatment actions, and optimizing the design of pavement geometry to reduce life-cycle greenhouse gas emissions.

Overall, the CSHub’s new streamlined pavement LCA method significantly improves the efficiency and accessibility of conducting pavement LCAs, making it easier for stakeholders to make informed decisions that enhance pavement performance and sustainability.

At this moment, there are approximately 35,000 tracked human-generated objects in orbit around Earth. Of these, only about one-third are active payloads: science and communications satellites, research experiments, and other beneficial technology deployments. The rest are categorized as debris — defunct satellites, spent rocket bodies, and the detritus of hundreds of collisions, explosions, planned launch vehicle separations, and other “fragmentation events” that have occurred throughout humanity’s 67 years of space launches. 

The problem of space debris is well documented, and only set to grow in the near term as launch rates increase and fragmentation events escalate accordingly. The clutter of debris — which includes an estimated 1 million objects over 1 centimeter, in addition to the tracked objects — regularly causes damage to satellites, requires the repositioning of the International Space Station, and has the potential to cause catastrophic collisions with increasing frequency. 

To address this issue, in 2019 the World Economic Forum selected a team co-led by MIT Associate Professor Danielle Wood’s Space Enabled Research Group at the MIT Media Lab to create a system for scoring space mission operators on their launch and de-orbit plans, collision-avoidance measures, debris generation, and data sharing, among other factors that would allow for better coordination and maintenance of space objects. The team has developed a system called the Space Sustainability Rating (SSR), and launched it in 2021 as an independent nonprofit. 

“Satellites provide valuable services that impact everyone in the world by helping us understand the environment, communicate globally, navigate, and operate our modern infrastructure. As innovative new missions are proposed that operate thousands of satellites, a new approach is needed to provide space traffic management. National governments and space operators need to design coordination approaches to reduce the risk of losing access to valuable satellite missions,” says Wood, who is jointly appointed in the Program in Media Arts and Sciences and the Department of Aeronautics and Astronautics (AeroAstro). “The Space Sustainability Rating plays a role by compiling internationally recognized responsible on-orbit behaviors, and celebrating space actors that implement them.” 

France-based Eutelsat Group, a geostationary Earth orbit and low Earth orbit satellite operator, signed on as the first constellation operator with a large deployment of satellites to undergo a rating. Eutelsat submitted a mission to SSR for assessment, and was rated on a tiered scoring system based on six performance modules. Eutelsat earned a platinum rating with a score exceeding 80 percent, indicating that the mission demonstrated exceptional sustainability in design, operations, and disposal practices.

As of December 2024, SSR has also provided ratings to operators such as OHB Sweden AB, Stellar, and TU Delft. 

In a new open-access paper published in Acta Astronautica, lead author Minoo Rathnasabapathy, Wood, and the SSR team provide the detailed history, motivation, and design of the Space Sustainability Rating as an incentive system that provides a score for space operators based on their effort to reduce space debris and collision risk. The researchers include AeroAstro alumnus Miles Lifson SM '20, PhD '24; University of Texas at Austin professor and former MIT MLK Scholar Moriba Jah; and collaborators from the European Space Agency, BryceTech, and the Swiss Institute of Technology of Lausanne Space Center (eSpace).

The paper provides transparency about the inception of SSR as a cross-organizational collaboration and its development as a composite indicator that evaluates missions across multiple quantifiable factors. The aim of SSR is to provide actionable feedback and a score recognizing operators’ contributions to the space sustainability effort. The paper also addresses the challenges SSR faces in adoption and implementation, and its alignment with various international space debris mitigation guidelines. 

SSR draws heavily on proven rating methodologies from other industries, particularly Leadership in Energy and Environmental Design (LEED) in the building and manufacturing industries, Sustainability Assessment of Food and Agriculture systems (SAFA) in the agriculture industry, and Sustainability Tracking, Assessment and Rating System (STARS) in the education industry. 

“By grounding SSR in quantifiable metrics and testing it across diverse mission profiles, we created a rating system that recognizes sustainable decisions and operations by satellite operators, aligned with international guidelines and industry best practices,” says Rathnasabapathy. 

The Space Sustainability Rating is a nongovernmental approach to encourage space mission operators to take responsible actions to reduce space debris and collision risk. The paper highlights the roles for private sector space operators and public sector space regulators to put steps in place to ensure such responsible actions are pursued. 

The Space Enabled Research Group continues to perform academic research that illustrates the benefits of space missions and government oversight bodies enforcing sustainable and safe space practices. Future work will highlight the need for a sustainability focus as practices such as satellite service and in-space manufacturing start to become more common. 

Dimitris Bertsimas SM ’87, PhD ’88, a leading figure in operations research, has been named the recipient of the 2025-26 James R. Killian Jr. Faculty Achievement Award. It is the highest honor the MIT faculty grants to its own professors.

Bertsimas is the Boeing Professor of Operations Research at the MIT Sloan School of Management, where he has made substantial contributions to business practices in many fields. He has also been a prolific advisor of graduate students and an enterprising leader of academic programs, serving as the inaugural faculty director of the Master of Business Analytics (MBAn) program since 2016, associate dean of business analytics since 2019, and vice provost for open learning since 2024.

“To be recognized among the group of Killian Award winners is a very humbling experience,” Bertsimas says. “I love this institution. This is where I have spent the last 40 years of my life. We don’t do things at MIT to get awards; we do things here because we believe they are important. It’s definitely something I’m proud of, but I’m also humbled to be in the company of many of my heroes.”

The Killian Award citation states that Bertsimas, “through his remarkable intellectual breadth and accomplishments, incredible productivity, outstanding contributions to theory and practice, and educational leadership, has made enormous contributions to his profession, the Institute, and the world.” It also notes that his “scholarly contributions are both vast and groundbreaking.”

Bertsimas received his BS in electrical engineering and computer science from the National Technical University of Athens in Greece. He moved to MIT in 1985 for his graduate work, earning his MS in operations research and his PhD in applied mathematics and operations research. After completing his doctoral work in 1988, Bertsimas joined the MIT faculty, and has remained at the Institute ever since.

A powerhouse researcher, Bertsimas has tackled a wide range of problems during his career. One area of his work has focused on optimization, the development of mathematical tools to help business operations be as efficient and logical as possible. Another focus of his scholarship has been machine learning and its interaction with optimization as well as stochastic systems. Overall, Bertsimas has developed the concepts and tools of “robust optimization,” allowing people to make better decisions under uncertainty.

At times in his career, Bertsimas has focused on health care issues, examining how machine learning can be used to develop more tools for personalized medical care. But all told, Bertsimas’ work has long been applied across many industries, from medicine to finance, energy, and beyond. The fingerprints of his research can be found in financial portfolios, school bus routing, supply chain logistics, energy use, medical data mining, diabetes management, and more.

“My strategy has been to address significant challenges that the world faces, and try to make progress,” Bertsimas says.

A dedicated educator, Bertsimas has been the principal doctoral thesis advisor to 103 MIT PhD students as of this spring. Lately he has been advising about five doctoral students per year, a remarkable number.

“Working with my doctoral students is my principal and most favorite activity,” Bertsimas says. “Second, in my research, I’ve tried to address problems that I think are important. If you solve them, something changes, in what we teach or in industry, and in short order. Not in 50 years, but in two years. Third, I feel it’s my obligation to educate — not only to create new knowledge, but to transmit it.”

As such, Bertsimas has been the founder and driving force behind MIT Sloan’s leading-edge MBAn program, and has thrown himself into leading MIT’s Open Learning efforts over the past year. He has also founded 10 data analytics companies during his career, while co-authoring hundreds of papers and eight graduate-level textbooks on data analytics.

The Killian Award was founded in 1971 in recognition of “extraordinary professional accomplishments by full-time members of the MIT faculty,” as the citation notes. The award is named after James R. Killian Jr., who served as president of MIT from 1948 to 1959 and as chair of the MIT Corporation from 1959 to 1971.

By tradition, Bertsimas will give a lecture in spring 2026 about his work.

The Killian Award is the latest honor in Bertsimas’ career. In 2019, he received the John von Neumann Theory Prize from INFORMS, the Institute for Operations Research and Management Science, for his contributions to the theory of operations research and the management sciences. He also received the INFORMS President’s Award in 2019 for his contributions to societal welfare. Bertsimas was elected to be a member of the National Academy of Engineering at age 43.

Reflecting on his career so far, Bertsimas emphasizes that he operates on a philosophy centered around positive thinking, high aspirations, and a can-do attitude applied to making a difference in the world for other people. Bertsimas praised MIT Sloan and the Operations Research Center as ideal places for him to pursue his work, due to its interdisciplinary nature, the quality of the students, and its openness to founding firms based on breakthrough work.

“I have been very happy at Sloan,” Bertsimas says. “It gives me the opportunity to work on things that are important with exceptional students predominantly from the Operations Research Center, and encourages my entrepreneurial spirit. Being at MIT Sloan and at the Operations Research Center has made a material difference in my career and my life.”

MIT alumnus Steven Troung ’20 has been awarded a 2025 Knight-Hennessy Scholarship and will join the eighth cohort of the prestigious fellowship. Knight-Hennessy Scholars receive up to three years of financial support for graduate studies at Stanford University.

Knight-Hennessy Scholars are selected for their independence of thought, purposeful leadership, and civic mindset. Troung is dedicated to making scientific advances in metabolic disorders, specifically diabetes, a condition that has affected many of his family members.

Truong, the son of Vietnamese refugees, originally hails from Minneapolis and graduated from MIT in 2020 with bachelor’s degrees in biological engineering and creative writing. During his time at MIT, Truong conducted research on novel diabetes therapies with professors Daniel Anderson and Robert Langer at the Koch Institute for Integrative Cancer Research and with Professor Douglas Lauffenburger in the Department of Biological Engineering.

Troung also founded a diabetes research project in Vietnam and co-led Vietnam’s largest genome-wide association study with physicians at the University of Medicine and Pharmacy in Ho Chi Minh City, where the team investigated the genetic determinants of Type 2 diabetes.

In his senior year at MIT, Truong won a Marshall Scholarship for post-graduate studies in the U.K. As a Marshall Scholar, he completed an MPhil in computational biology at Cambridge University and an MA in creative writing at Royal Holloway, University of London. Troung is currently pursuing an MD and a PhD in biophysics at the Stanford School of Medicine.

In addition to winning a Knight-Hennessy Scholarship and the Marshall Scholarship, Truong was the recipient of a 2019-20 Goldwater Scholarship and a 2023 Paul and Daisy Soros Fellowship for New Americans.

Students interested in applying to the Knight-Hennessy Scholars program can contact Kim Benard, associate dean of distinguished fellowships in Career Advising and Professional Development. 

The winner of this year’s MIT $100K Entrepreneurship Competition is helping advanced therapies reach more patients faster with a new kind of drug-injection device.

CoFlo Medical says its low-cost device can deliver biologic drugs more than 10 times faster than existing methods, accelerating the treatment of a range of conditions including cancers, autoimmune diseases, and infectious diseases.

“For patients battling these diseases, every hour matters,” said Simon Rufer SM ’22 in the winning pitch. “Biologic drugs are capable of treating some of the most challenging diseases, but their administration is unacceptably time-consuming, infringing on the freedom of the patient and effectively leaving them tethered to their hospital beds. The requirement of a hospital setting also makes biologics all but impossible in remote and low-access areas.”

Today, biologic drugs are mainly delivered through intravenous fusions, requiring patients to sit in hospital beds for hours during each delivery. That’s because many biologic drugs are too viscous to be pushed through a needle. CoFlo’s device enables quick injections of biologic drugs no matter how viscous. It works by surrounding the viscous drug with a second, lower-viscosity fluid.

“Imagine trying to force a liquid as viscous as honey through a needle: It’s simply not possible,” said Rufer, who is currently a PhD candidate in the Department of Mechanical Engineering. “Over the course of six years of research and development at MIT, we’ve overcome a myriad of fluidic instabilities that have otherwise made this technology impossible. We’ve also patented the fundamental inner workings of this device.”

Rufer made the winning pitch to a packed Kresge Auditorium that included a panel of judges on May 12. In a video, he showed someone injecting biologic drugs using CoFlo’s device using one hand.

Rufer says the second fluid in the device could be the buffer of the drug solution itself, which wouldn’t alter the drug formulation and could potentially expedite the device’s approval in clinical trials. The device can also easily be made using existing mass manufacturing processes, which will keep the cost low.

In laboratory experiments, CoFlo’s team has demonstrated injections that are up to 200 times faster.

“CoFlo is the only technology that is capable of administering viscous drugs while simultaneously optimizing the patient experience, minimizing the clinical burden, and reducing device cost,” Rufer said.

Celebrating entrepreneurship

The MIT $100K Competition started more than 30 years ago, when students, along with the late MIT Professor Ed Roberts, raised $10,000 to turn MIT’s “mens et manus” (“mind and hand”) motto into a startup challenge. Over time, with sponsor support, the event grew into the renown, highly anticipated startup competition it is today, highlighting some of the most promising new companies founded by MIT community members each year.

The Monday night event was the culmination of months of work and preparation by participating teams. The $100K program began with student pitches in December and was followed by mentorship, funding, and other support for select teams over the course of ensuing months.

This year more than 50 teams applied for the $100K’s final event. A network of external judges whittled that down to the eight finalists that made their pitches.

Other winners

In addition to the grand prize, finalists were also awarded a $50,000 second-place prize, a $5,000 third-place prize, and a $5,000 audience choice award, which was voted on during the judge’s deliberations.

The second-place prize went to Haven, an artificial intelligence-powered financial planning platform that helps families manage lifelong disability care. Haven’s pitch was delivered by Tej Mehta, a student in the MIT Sloan School of Management who explained the problem by sharing his own family’s experience managing his sister’s intellectual disability.

“As my family plans for the future, a number of questions are keeping us up at night,” Mehta told the audience. “How much money do we need to save? What public benefits is she eligible for? How do we structure our private assets so she doesn’t lose those public benefits? Finally, how do we manage the funds and compliance over time?”

Haven works by using family information and goals to build a personalized roadmap that can predict care needs and costs over more than 50 years.

“We recommend to families the exact next steps they need to take, what to apply for, and when,” Mehta explained.

The third-place prize went to Aorta Scope, which combines AI and ultrasound to provide augmented reality guidance during vascular surgery. Today, surgeons must rely on a 2-D X-ray image as they feed a large stent into patients’ body during a common surgery known as endovascular repair.

Aorta Scope has developed a platform for real-time, 3-D implant alignment. The solution combines intravascular ultrasound technology with fiber optic shape sensing. Tom Dillon built the system that combines data from those sources as part of his ongoing PhD in MIT’s Department of Mechanical Engineering.

Finally, the audience choice award went to Flood Dynamics, which provides real-time flood risk modeling to help cities, insurers, and developers adapt and protect urban communities from flooding.

Although most urban flood damages are driven by rain today, flood models don’t account for rainfall, making cities less prepared for flooding risks.

“Flooding, and especially rain-driven flooding, is the costliest natural hazard around the world today,” said Katerina Boukin SM ’20, PhD ’25, who developed the company’s technology at MIT. “The price of staying rain-blind is really steep. This is an issue that is costing the U.S. alone more than $30 billion a year.”

Imagine a radiologist examining a chest X-ray from a new patient. She notices the patient has swelling in the tissue but does not have an enlarged heart. Looking to speed up diagnosis, she might use a vision-language machine-learning model to search for reports from similar patients.

But if the model mistakenly identifies reports with both conditions, the most likely diagnosis could be quite different: If a patient has tissue swelling and an enlarged heart, the condition is very likely to be cardiac related, but with no enlarged heart there could be several underlying causes.

In a new study, MIT researchers have found that vision-language models are extremely likely to make such a mistake in real-world situations because they don’t understand negation — words like “no” and “doesn’t” that specify what is false or absent. 

“Those negation words can have a very significant impact, and if we are just using these models blindly, we may run into catastrophic consequences,” says Kumail Alhamoud, an MIT graduate student and lead author of this study.

The researchers tested the ability of vision-language models to identify negation in image captions. The models often performed as well as a random guess. Building on those findings, the team created a dataset of images with corresponding captions that include negation words describing missing objects.

They show that retraining a vision-language model with this dataset leads to performance improvements when a model is asked to retrieve images that do not contain certain objects. It also boosts accuracy on multiple choice question answering with negated captions.

But the researchers caution that more work is needed to address the root causes of this problem. They hope their research alerts potential users to a previously unnoticed shortcoming that could have serious implications in high-stakes settings where these models are currently being used, from determining which patients receive certain treatments to identifying product defects in manufacturing plants.

“This is a technical paper, but there are bigger issues to consider. If something as fundamental as negation is broken, we shouldn’t be using large vision/language models in many of the ways we are using them now — without intensive evaluation,” says senior author Marzyeh Ghassemi, an associate professor in the Department of Electrical Engineering and Computer Science (EECS) and a member of the Institute of Medical Engineering Sciences and the Laboratory for Information and Decision Systems.

Ghassemi and Alhamoud are joined on the paper by Shaden Alshammari, an MIT graduate student; Yonglong Tian of OpenAI; Guohao Li, a former postdoc at Oxford University; Philip H.S. Torr, a professor at Oxford; and Yoon Kim, an assistant professor of EECS and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. The research will be presented at Conference on Computer Vision and Pattern Recognition.

Neglecting negation

Vision-language models (VLM) are trained using huge collections of images and corresponding captions, which they learn to encode as sets of numbers, called vector representations. The models use these vectors to distinguish between different images.

A VLM utilizes two separate encoders, one for text and one for images, and the encoders learn to output similar vectors for an image and its corresponding text caption.

“The captions express what is in the images — they are a positive label. And that is actually the whole problem. No one looks at an image of a dog jumping over a fence and captions it by saying ‘a dog jumping over a fence, with no helicopters,’” Ghassemi says.

Because the image-caption datasets don’t contain examples of negation, VLMs never learn to identify it.

To dig deeper into this problem, the researchers designed two benchmark tasks that test the ability of VLMs to understand negation.

For the first, they used a large language model (LLM) to re-caption images in an existing dataset by asking the LLM to think about related objects not in an image and write them into the caption. Then they tested models by prompting them with negation words to retrieve images that contain certain objects, but not others.

For the second task, they designed multiple choice questions that ask a VLM to select the most appropriate caption from a list of closely related options. These captions differ only by adding a reference to an object that doesn’t appear in the image or negating an object that does appear in the image.

The models often failed at both tasks, with image retrieval performance dropping by nearly 25 percent with negated captions. When it came to answering multiple choice questions, the best models only achieved about 39 percent accuracy, with several models performing at or even below random chance.

One reason for this failure is a shortcut the researchers call affirmation bias — VLMs ignore negation words and focus on objects in the images instead.

“This does not just happen for words like ‘no’ and ‘not.’ Regardless of how you express negation or exclusion, the models will simply ignore it,” Alhamoud says.

This was consistent across every VLM they tested.

“A solvable problem”

Since VLMs aren’t typically trained on image captions with negation, the researchers developed datasets with negation words as a first step toward solving the problem.

Using a dataset with 10 million image-text caption pairs, they prompted an LLM to propose related captions that specify what is excluded from the images, yielding new captions with negation words.

They had to be especially careful that these synthetic captions still read naturally, or it could cause a VLM to fail in the real world when faced with more complex captions written by humans.

They found that finetuning VLMs with their dataset led to performance gains across the board. It improved models’ image retrieval abilities by about 10 percent, while also boosting performance in the multiple-choice question answering task by about 30 percent.

“But our solution is not perfect. We are just recaptioning datasets, a form of data augmentation. We haven’t even touched how these models work, but we hope this is a signal that this is a solvable problem and others can take our solution and improve it,” Alhamoud says.

At the same time, he hopes their work encourages more users to think about the problem they want to use a VLM to solve and design some examples to test it before deployment.

In the future, the researchers could expand upon this work by teaching VLMs to process text and images separately, which may improve their ability to understand negation. In addition, they could develop additional datasets that include image-caption pairs for specific applications, such as health care.

The MIT Press has announced that beginning in 2026, Duke University Press will join its Direct to Open (D2O) program. This collaboration marks the first such partnership with another university press for the D2O program, and reaffirms their shared commitment to open access publishing that is ethical, equitable, and sustainable.

Launched in 2021, D2O is the MIT Press’ framework for open access monographs that shifts publishing from a solely market-based purchase model, where individuals and libraries buy single e-books, to a collaborative, library-supported open access model. 

Duke University Press brings their distinguished catalog in the humanities and social sciences to Direct to Open, providing open access to 20 frontlist titles annually alongside the MIT Press’ 80 scholarly books each year. Their participation in the D2O program — which will also include free term access to a paywalled collection of 250 key backlist titles — enhances the range of openly available academic content for D2O’s library partners.

“By expanding the Direct to Open model to include one of the most innovative university presses publishing today, we’re taking a significant step toward building a more open and accessible future for academic publishing,” says Amy Brand, director and publisher of the MIT Press. “We couldn’t be more thrilled to be building this partnership with Duke University Press. This collaboration will benefit the entire scholarly community, ensuring that more books are made openly available to readers worldwide.”

“We are honored to participate in MIT Press’ dynamic and successful D2O program,” says Dean Smith, director of Duke University Press. “It greatly expands our open-access footprint and serves our mission of making bold and transformational scholarship accessible to the world.”

With Duke University Press’ involvement in 2026, D2O will feature multiple package options, combining content from both the MIT Press and Duke University Press. Participating institutions will have the opportunity to support each press individually, providing flexibility for libraries while fostering collective impact.

For details on how your institution might participate in or support Direct to Open, please visit the D2O website or contact the MIT Press library relations team.  

Starting in July, MIT’s Shaping the Future of Work Initiative in the Department of Economics will usher in a significant new era of research, policy, and education of the next generation of scholars, made possible by a gift from the James M. and Cathleen D. Stone Foundation. In recognition of the gift and the expansion of priorities it supports, on July 1 the initiative will become part of the new James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work. This center will be officially launched at a public event in fall 2025.

The Stone Center will be led by Daron Acemoglu, Institute Professor, and co-directors David Autor, the Daniel (1972) and Gail Rubinfeld Professor in Economics, and Simon Johnson, the Ronald A. Kurtz (1954) Professor of Entrepreneurship. It will join a global network of 11 other wealth inequality centers funded by the Stone Foundation as part of an effort to advance research on the causes and consequences of the growing accumulation at the top of the wealth distribution.

“This generous gift from the Stone Foundation advances our pioneering economics research on inequality, technology, and the future of the workforce. This work will create a pipeline of scholars in this critical area of study, and it will help to inform the public and policymakers,” says Provost Cynthia Barnhart.

Originally established as part of MIT Blueprint Labs with a foundational gift from the William and Flora Hewlett Foundation, the Shaping the Future of Work Initiative is a nonpartisan research organization that applies economics research to identify innovative ways to move the labor market onto a more equitable trajectory, with a central focus on revitalizing labor market opportunities for workers without a college education. Building on frontier micro- and macro-economics, economic sociology, political economy, and other disciplines, the initiative seeks to answer key questions about the decline in labor market opportunities for non-college workers in recent decades. These labor market changes have been a major driver of growing wealth inequality, a phenomenon that has, in turn, broadly reshaped our economy, democracy, and society.

Support from the Stone Foundation will allow the new Stone Center to build on the Shaping the Future of Work Initiative’s ongoing research agenda and extend its focus to include a growing emphasis on the interplay between technologies and inequality, as well as the technology sector’s role in defining future inequality.

Core objectives of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work will include fostering connections between scholars doing pathbreaking research on automation, AI, the intersection of work and technology, and wealth inequality across disciplines, including within the Department of Economics, the MIT Sloan School of Management, and the MIT Stephen A. Schwarzman College of Computing; strengthening the pipeline of emerging scholars focused on these issues; and using research to inform and engage a wider audience including the public, undergraduate and graduate students, and policymakers.     

The Stone Foundation’s support will allow the center to strengthen and expand its commitments to produce new research, convene additional events to share research findings, promote connection and collaboration between scholars working on related topics, provide new resources for the center’s research affiliates, and expand public outreach to raise awareness of this important emerging challenge. “Cathy and I are thrilled to welcome MIT to the growing family of Stone Centers dedicated to studying the urgent challenges of accelerating wealth inequality,” James M. Stone says.

Agustín Rayo, dean of the School of Humanities, Arts, and Social Sciences, says, “I am thrilled to celebrate the creation of the James M. and Cathleen D. Stone Center in the MIT economics department. Not only will it enhance the cutting-edge work of MIT’s social scientists, but it will support cross-disciplinary interactions that will enable new insights and solutions to complex social challenges.”

Jonathan Gruber, chair of the Department of Economics, adds, “I couldn’t be more excited about the Stone Foundation’s support for the Shaping the Future of Work Initiative. The initiative’s leaders have been far ahead of the curve in anticipating the rapid changes that technological forces are bringing to the labor market, and their influential studies have helped us understand the potential effects of AI and other technologies on U.S. workers. The generosity of the Stone Foundation will allow them to continue this incredible work, while expanding their priorities to include other critical issues around inequality. This is a great moment for the paradigm-shifting research that Acemoglu, Autor, and Johnson are leading here at MIT.”

“We are grateful to the James M. and Cathleen D. Stone Foundation for their generous support enabling us to study two defining challenges of our age: inequality and the future of work,” says Acemoglu, who was awarded the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel in 2024 (with co-laureates Simon Johnson and James A. Robinson). “We hope to go beyond exploring the causes of inequality and the determinants of the availability of good jobs in the present and in the future, but also develop ideas about how society can shape both the work of the future and inequality by its choices of institutions and technological trajectories.”

“We are incredibly fortunate to be joining the family of Stone Centers around the world. Jim and Cathleen Stone are far-sighted and generous donors, and we are delighted that they are willing to back us and MIT in this way,” says Johnson. “We look forward to working with all our colleagues, at MIT and around the world, to advance understanding and practical approaches to inequality and the future of work.”

Autor adds, “This support will enable us — and many others — to focus our scholarship, teaching and public outreach towards shaping a labor market that offers opportunity, mobility, and economic security to a far broader set of people.” 

Just 10 to 15 minutes of mindfulness practice a day led to reduced stress and anxiety for autistic adults who participated in a study led by scientists at MIT’s McGovern Institute for Brain Research. Participants in the study used a free smartphone app to guide their practice, giving them the flexibility to practice when and where they chose.

Mindfulness is a state in which the mind is focused only on the present moment. It is a way of thinking that can be cultivated with practice, often through meditation or breathing exercises — and evidence is accumulating that practicing mindfulness has positive effects on mental health. The new open-access study, reported April 8 in the journal Mindfulness, adds to that evidence, demonstrating clear benefits for autistic adults.

“Everything you want from this on behalf of somebody you care about happened: reduced reports of anxiety, reduced reports of stress, reduced reports of negative emotions, and increased reports of positive emotions,” says McGovern investigator and MIT Professor John Gabrieli, who led the research with Liron Rozenkrantz, an investigator at the Azrieli Faculty of Medicine at Bar-Ilan University in Israel and a research affiliate in Gabrieli’s lab. “Every measure that we had of well-being moved in significantly in a positive direction,” adds Gabrieli, who is also the Grover Hermann Professor of Health Sciences and Technology and a professor of brain and cognitive sciences at MIT.

One of the reported benefits of practicing mindfulness is that it can reduce the symptoms of anxiety disorders. This prompted Gabrieli and his colleagues to wonder whether it might benefit adults with autism, who tend to report above average levels of anxiety and stress, which can interfere with daily living and quality of life. As many as 65 percent of autistic adults may also have an anxiety disorder.

Gabrieli adds that the opportunity for autistic adults to practice mindfulness with an app, rather than needing to meet with a teacher or class, seemed particularly promising. “The capacity to do it at your own pace in your own home, or any environment you like, might be good for anybody,” he says. “But maybe especially for people for whom social interactions can sometimes be challenging.”

The research team, including Cindy Li, the autism recruitment and outreach coordinator in Gabrieli’s lab, recruited 89 autistic adults to participate in their study. Those individuals were split into two groups: one would try the mindfulness practice for six weeks, while the others would wait and try the intervention later.

Participants were asked to practice daily using an app called Healthy Minds, which guides participants through seated or active meditations, each lasting 10 to 15 minutes. Participants reported that they found the app easy to use and had little trouble making time for the daily practice.

After six weeks, participants reported significant reductions in anxiety and perceived stress. These changes were not experienced by the wait-list group, which served as a control. However, after their own six weeks of practice, people in the wait-list group reported similar benefits. “We replicated the result almost perfectly. Every positive finding we found with the first sample we found with the second sample,” Gabrieli says.

The researchers followed up with study participants after another six weeks. Almost everyone had discontinued their mindfulness practice — but remarkably, their gains in well-being had persisted. Based on this finding, the team is eager to further explore the long-term effects of mindfulness practice in future studies. “There’s a hypothesis that a benefit of gaining mindfulness skills or habits is they stick with you over time — that they become incorporated in your daily life,” Gabrieli says. “If people are using the approach to being in the present and not dwelling on the past or worrying about the future, that’s what you want most of all. It’s a habit of thought that’s powerful and helpful.”

Even as they plan future studies, the researchers say they are already convinced that mindfulness practice can have clear benefits for autistic adults. “It’s possible mindfulness would be helpful at all kinds of ages,” Gabrieli says. But he points out the need is particularly great for autistic adults, who usually have fewer resources and support than autistic children have access to through their schools. Gabrieli is eager for more people with autism to try the Healthy Minds app. “Having scientifically proven resources for adults who are no longer in school systems might be a valuable thing,” he says.

This research was funded, in part, by The Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT and the Yang Tan Collective.

How should personal data be protected? What are the best uses of it? In our networked world, questions about data privacy are ubiquitous and matter for companies, policymakers, and the public.

A new study by MIT researchers adds depth to the subject by suggesting that people’s views about privacy are not firmly fixed and can shift significantly, based on different circumstances and different uses of data.

“There is no absolute value in privacy,” says Fabio Duarte, principal research scientist in MIT’s Senseable City Lab and co-author of a new paper outlining the results. “Depending on the application, people might feel use of their data is more or less invasive.”

The study is based on an experiment the researchers conducted in multiple countries using a newly developed game that elicits public valuations of data privacy relating to different topics and domains of life.

“We show that values attributed to data are combinatorial, situational, transactional, and contextual,” the researchers write.

The open-access paper, “Data Slots: tradeoffs between privacy concerns and benefits of data-driven solutions,” is published today in Nature: Humanities and Social Sciences Communications. The authors are Martina Mazzarello, a postdoc in the Senseable City Lab; Duarte; Simone Mora, a research scientist at Senseable City Lab; Cate Heine PhD ’24 of University College London; and Carlo Ratti, director of the Senseable City Lab.

The study is based around a card game with poker-type chips the researchers created to study the issue, called Data Slots. In it, players hold hands of cards with 12 types of data — such as a personal profile, health data, vehicle location information, and more — that relate to three types of domains where data are collected: home life, work, and public spaces. After exchanging cards, the players generate ideas for data uses, then assess and invest in some of those concepts. The game has been played in-person in 18 different countries, with people from another 74 countries playing it online; over 2,000 individual player-rounds were included in the study.

The point behind the game is to examine the valuations that members of the public themselves generate about data privacy. Some research on the subject involves surveys with pre-set options that respondents choose from. But in Data Slots, the players themselves generate valuations for a wide range of data-use scenarios, allowing the researchers to estimate the relative weight people place on privacy in different situations. 

The idea is “to let people themselves come up with their own ideas and assess the benefits and privacy concerns of their peers’ ideas, in a participatory way,” Ratti explains.

The game strongly suggests that people’s ideas about data privacy are malleable, although the results do indicate some tendencies. The data privacy card whose use players most highly valued was for personal mobility; given the opportunity in the game to keep it or exchange it, players retained it in their hands 43 percent of the time, an indicator of its value. That was followed in order by personal health data, and utility use. (With apologies to pet owners, the type of data privacy card players held on to the least, about 10 percent of the time, involved animal health.)

However, the game distinctly suggests that the value of privacy is highly contingent on specific use-cases. The game shows that people care about health data to a substantial extent but also value the use of environmental data in the workplace, for instance. And the players of Data Slots also seem less concerned about data privacy when use of data is combined with clear benefits. In combination, that suggests a deal to be cut: Using health data can help people understand the effects of the workplace on wellness.

“Even in terms of health data in work spaces, if they are used in an aggregated way to improve the workspace, for some people it’s worth combining personal health data with environmental data,” Mora says.

Mazzarello adds: “Now perhaps the company can make some interventions to improve overall health. It might be invasive, but you might get some benefits back.”

In the bigger picture, the researchers suggest, taking a more flexible, user-driven approach to understanding what people think about data privacy can help inform better data policy. Cities — the core focus on the Senseable City Lab — often face such scenarios. City governments can collect a lot of aggregate traffic data, for instance, but public input can help determine how anonymized such data should be. Understanding public opinion along with the benefits of data use can produce viable policies for local officials to pursue.

“The bottom line is that if cities disclose what they plan to do with data, and if they involve resident stakeholders to come up with their own ideas about what they could do, that would be beneficial to us,” Duarte says. “And in those scenarios, people’s privacy concerns start to decrease a lot.” 

The United States population is older than it has ever been. Today, the country’s median age is 38.9, which is nearly a decade older than it was in 1980. And the number of adults older than 65 is expected to balloon from 58 million to 82 million by 2050. The challenge of caring for the elderly, amid shortages in care workers, rising health care costs, and evolving family structures, is an increasingly urgent societal issue.

To help address the eldercare challenge, a team of MIT engineers is looking to robotics. They have built and tested the Elderly Bodily Assistance Robot, or E-BAR, a mobile robot designed to physically support the elderly and prevent them from falling as they move around their homes.

E-BAR acts as a set of robotic handlebars that follows a person from behind. A user can walk independently or lean on the robot’s arms for support. The robot can support the person’s full weight, lifting them from sitting to standing and vice versa along a natural trajectory. And the arms of the robot can them by rapidly inflating side airbags if they begin to fall.

With their design, the researchers hope to prevent falls, which today are the leading cause of injury in adults who are 65 and older. 

“Many older adults underestimate the risk of fall and refuse to use physical aids, which are cumbersome, while others overestimate the risk and may not to exercise, leading to declining mobility,” says Harry Asada, the Ford Professor of Engineering at MIT. “Our design concept is to provide older adults having balance impairment with robotic handlebars for stabilizing their body. The handlebars go anywhere and provide support anytime, whenever they need.”

In its current version, the robot is operated via remote control. In future iterations, the team plans to automate much of the bot’s functionality, enabling it to autonomously follow and physically assist a user. The researchers are also working on streamlining the device to make it slimmer and more maneuverable in small spaces.

“I think eldercare is the next great challenge,” says E-BAR designer Roberto Bolli, a graduate student in the MIT Department of Mechanical Engineering. “All the demographic trends point to a shortage of caregivers, a surplus of elderly persons, and a strong desire for elderly persons to age in place. We see it as an unexplored frontier in America, but also an intrinsically interesting challenge for robotics.”

Bolli and Asada will present a paper detailing the design of E-BAR at the IEEE Conference on Robotics and Automation (ICRA) later this month.

Asada’s group at MIT develops a variety of technologies and robotic aides to assist the elderly. In recent years, others have developed fall prediction algorithms, designed robots and automated devices including robotic walkers, wearable, self-inflating airbags, and robotic frames that secure a person with a harness and move with them as they walk.

In designing E-BAR, Asada and Bolli aimed for a robot that essentially does three tasks: providing physical support, preventing falls, and safely and unobtrusively moving with a person. What’s more, they looked to do away with any harness, to give a user more independence and mobility.

“Elderly people overwhelmingly do not like to wear harnesses or assistive devices,” Bolli says. “The idea behind the E-BAR structure is, it provides body weight support, active assistance with gait, and fall catching while also being completely unobstructed in the front. You can just get out anytime.”

The team looked to design a robot specifically for aging in place at home or helping in care facilities. Based on their interviews with older adults and their caregivers, they came up with several design requirements, including that the robot must fit through home doors, allow the user to take a full stride, and support their full weight to help with balance, posture, and transitions from sitting to standing.

The robot consists of a heavy, 220-pound base whose dimensions and structure were optimized to support the weight of an average human without tipping or slipping. Underneath the base is a set of omnidirectional wheels that allows the robot to move in any direction without pivoting, if needed. (Imagine a car’s wheels shifting to slide into a space between two other cars, without parallel parking.)

Extending out from the robot’s base is an articulated body made from 18 interconnected bars, or linkages, that can reconfigure like a foldable crane to lift a person from a sitting to standing position, and vice versa. Two arms with handlebars stretch out from the robot in a U-shape, which a person can stand between and lean against if they need additional support. Finally, each arm of the robot is embedded with airbags made from a soft yet grippable material that can inflate instantly to catch a person if they fall, without causing bruising on impact. The researchers believe that E-BAR is the first robot able to catch a falling person without wearable devices or use of a harness.

They tested the robot in the lab with an older adult who volunteered to use the robot in various household scenarios. The team found that E-BAR could actively support the person as they bent down to pick something up from the ground and stretched up to reach an object off a shelf — tasks that can be challenging to do while maintaining balance. The robot also was able to lift the person up and over the lip of a tub, simulating the task of getting out of a bathtub.

Bolli envisions a design like E-BAR would be ideal for use in the home by elderly people who still have a moderate degree of muscle strength but require assistive devices for activities of daily living.

“Seeing the technology used in real-life scenarios is really exciting,” says Bolli.

In their current paper, the researchers did not incorporate any fall-prediction capabilities in E-BAR’s airbag system. But another project in Asada’s lab, led by graduate student Emily Kamienski, has focused on developing algorithms with machine learning to control a new robot in response to the user’s real-time fall risk level.

Alongside E-BAR, Asada sees different technologies in his lab as providing different levels of assistance for people at certain phases of life or mobility.

“Eldercare conditions can change every few weeks or months,” Asada says. “We’d like to provide continuous and seamless support as a person’s disability or mobility changes with age.”

This work was supported, in part, by the National Robotics Initiative and the National Science Foundation.

Studies by a growing number of labs have identified neurological health benefits from exposing human volunteers or animal models to light, sound, and/or tactile stimulation at the brain’s “gamma” frequency rhythm of 40Hz. In the latest such research at The Picower Institute for Learning and Memory and Alana Down Syndrome Center at MIT, scientists found that 40Hz sensory stimulation improved cognition and circuit connectivity and encouraged the growth of new neurons in mice genetically engineered to model Down syndrome.

Li-Huei Tsai, Picower Professor at MIT and senior author of the new study in PLOS ONE, says that the results are encouraging, but also cautions that much more work is needed to test whether the method, called GENUS (for gamma entrainment using sensory stimulation), could provide clinical benefits for people with Down syndrome. Her lab has begun a small study with human volunteers at MIT.

“While this work, for the first time, shows beneficial effects of GENUS on Down syndrome using an imperfect mouse model, we need to be cautious, as there is not yet data showing whether this also works in humans,” says Tsai, who directs The Picower Institute and The Alana Center, and is a member of MIT’s Department of Brain and Cognitive Sciences faculty.

Still, she says, the newly published article adds evidence that GENUS can promote a broad-based, restorative, “homeostatic” health response in the brain amid a wide variety of pathologies. Most GENUS studies have addressed Alzheimer’s disease in humans or mice, but others have found benefits from the stimulation for conditions such as “chemo brain” and stroke.

Down syndrome benefits

In the study, the research team led by postdoc Md Rezaul Islam and Brennan Jackson PhD ’23 worked with the commonly used “Ts65Dn” Down syndrome mouse model. The model recapitulates key aspects of the disorder, although it does not exactly mirror the human condition, which is caused by carrying an extra copy of chromosome 21.

In the first set of experiments in the paper, the team shows that an hour a day of 40Hz light and sound exposure for three weeks was associated with significant improvements on three standard short-term memory tests — two involving distinguishing novelty from familiarity and one involving spatial navigation. Because these kinds of memory tasks involve a brain region called the hippocampus, the researchers looked at neural activity there and measured a significant increase in activity indicators among mice that received the GENUS stimulation versus those that did not.

To better understand how stimulated mice could show improved cognition, the researchers examined whether cells in the hippocampus changed how they express their genes. To do this, the team used a technique called single cell RNA sequencing, which provided a readout of how nearly 16,000 individual neurons and other cells transcribed their DNA into RNA, a key step in gene expression. Many of the genes whose expression varied most prominently in neurons between the mice that received stimulation and those that did not were directly related to forming and organizing neural circuit connections called synapses.

To confirm the significance of that finding, the researchers directly examined the hippocampus in stimulated and control mice. They found that in a critical subregion, the dentate gyrus, stimulated mice had significantly more synapses.

Diving deeper

The team not only examined gene expression across individual cells, but also analyzed those data to assess whether there were patterns of coordination across multiple genes. Indeed, they found several such “modules” of co-expression. Some of this evidence further substantiated the idea that 40Hz-stimulated mice made important improvements in synaptic connectivity, but another key finding highlighted a role for TCF4, a key regulator of gene transcription needed for generating new neurons, or “neurogenesis.”  

The team’s analysis of genetic data suggested that TCF4 is underexpressed in Down syndrome mice, but the researchers saw improved TCF4 expression in GENUS-stimulated mice. When the researchers went to the lab bench to determine whether the mice also exhibited a difference in neurogenesis, they found direct evidence that stimulated mice exhibited more than unstimulated mice in the dentate gyrus. These increases in TCF4 expression and neurogenesis are only correlational, the researchers noted, but they hypothesize that the increase in new neurons likely helps explain at least some of the increase in new synapses and improved short-term memory function.

“The increased putative functional synapses in the dentate gyrus is likely related to the increased adult neurogenesis observed in the Down syndrome mice following GENUS treatment,” Islam says.

This study is the first to document that GENUS is associated with increased neurogenesis.

The analysis of gene expression modules also yielded other key insights. One is that a cluster of genes whose expression typically declines with normal aging, and in Alzheimer’s disease, remained at higher expression levels among mice who received 40Hz sensory stimulation.

And the researchers also found evidence that mice that received stimulation retained more cells in the hippocampus that express Reelin. Reelin-expressing neurons are especially vulnerable in Alzheimer’s disease, but expression of the protein is associated with cognitive resilience amid Alzheimer’s disease pathology, which Ts65Dn mice develop. About 90 percent of people with Down syndrome develop Alzheimer’s disease, typically after the age of 40.

“In this study, we found that GENUS enhances the percentage of Reln+ neurons in hippocampus of a mouse model of Down syndrome, suggesting that GENUS may promote cognitive resilience,” Islam says.

Taken together with other studies, Tsai and Islam say, the new results add evidence that GENUS helps to stimulate the brain at the cellular and molecular level to mount a homeostatic response to aberrations caused by disease pathology, be it neurodegeneration in Alzheimer’s, demyelination in chemo brain, or deficits of neurogenesis in Down syndrome.

But the authors also cautioned that the study had limits. Not only is the Ts65Dn model an imperfect reflection of human Down syndrome, but also the mice used were all male. Moreover, the cognitive tests in the study only measured short-term memory. And finally, while the study was novel for extensively examining gene expression in the hippocampus amid GENUS stimulation, it did not look at changes in other cognitively critical brain regions, such as the prefrontal cortex.

In addition to Jackson, Islam, and Tsai, the paper’s other authors are Maeesha Tasnim Naomi, Brooke Schatz, Noah Tan, Mitchell Murdock, Dong Shin Park, Daniela Rodrigues Amorim, Fred Jiang, S. Sebastian Pineda, Chinnakkaruppan Adaikkan, Vanesa Fernandez, Ute Geigenmuller, Rosalind Mott Firenze, Manolis Kellis, and Ed Boyden.

Funding for the study came from the Alana Down Syndrome Center at MIT and the Alana USA Foundation, the U.S. National Science Foundation, the La Caixa Banking Foundation, a European Molecular Biology Organization long-term postdoctoral fellowship, Barbara J. Weedon, Henry E. Singleton, and the Hubolow family.