As a college student in Serbia with a passion for math and physics, Ana Trišović found herself drawn to computer science and its practical, problem-solving approaches. It was then that she discovered MIT OpenCourseWare, part of MIT Open Learning, and decided to study a course on Data Analytics with Python in 2012 — something her school didn’t offer.

That experience was transformative, says Trišović, who is now a research scientist at the FutureTech lab within MIT’s Computer Science and Artificial Intelligence Laboratory.

“That course changed my life,” she says. “Throughout my career, I have considered myself a Python coder, and MIT OpenCourseWare made it possible. I was in my hometown on another continent, learning from MIT world-class resources. When I reflect on my path, it’s incredible.”

Over time, Trišović's path led her to explore a range of OpenCourseWare resources. She recalls that, as a non-native English speaker, some of the materials were challenging. But thanks to the variety of courses and learning opportunities available on OpenCourseWare, she was always able to find ones that suited her. She encourages anyone facing that same challenge to be persistent.

“If the first course doesn’t work for you, try another,” she says. “Being persistent and investing in yourself is the best thing a young person can do.”

In her home country of Serbia, Trišović earned undergraduate degrees in computer science and mechanical engineering before going on to Cambridge University and CERN, where she contributed to work on the Large Hadron Collider and completed her PhD in computer science in 2018. She has also done research at the University of Chicago and Harvard University.

“I like that computer science allows me to make an impact in a range of fields, but physics remains close to my heart, and I’m constantly inspired by it,” she says.

MIT FutureTech, an interdisciplinary research group, draws on computer science, economics, and management to identify computing trends that create risk and opportunities for sustainable economic growth. There, Trišović studies the democratization of AI, including the implications of open-source AI and how that will impact science. Her work at MIT is a chance to build on research she has been pursuing since she was in graduate school.

“My work focuses on computational social science. For many years, I’ve been looking at what's known as 'the science of science' — investigating issues like research reproducibility," Trišović explains. “Now, as AI becomes increasingly prevalent and introduces new challenges, I’m interested in examining a range of topics — from AI democratization to its effects on the scientific method and the broader landscape of science.”

Trišović is grateful that, way back in 2012, she made the decision to try something new and learn with an OpenCourseWare course.

“I instantly fell in love with Python the moment I took that course. I have such a soft spot for OpenCourseWare — it shaped my career,” she says. “Every day at MIT is inspiring. I work with people who are excited to talk about AI and other fascinating topics.”

In another rare squid/cybersecurity intersection, APT37 is also known as “Squid Werewolf.”

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Earlier this week, the House Judiciary Committee passed H.R. 1526, a bill by Rep. Darrell Issa to prevent courts from issuing nationwide injunctions. This bill could receive a vote on the House floor as early as next week. Senator Josh Hawley recently introduced a similar bill in the Senate. Both bills would prohibit district courts from handing down injunctive relief orders that apply to parties that are not involved in the case. 

EFF opposes both bills. We see this legislation for what it is: a transparent attempt to limit courts' ability to act as an effective check on the Trump administration’s recent flood of illegal orders and actions – some of which EFF itself is challenging. Congress should firmly oppose any effort to prevent the judicial branch from fulfilling its constitutional duty.

Indeed, this is a remedy in search of a problem. There are already well-established tests for injunctive relief: Courts must consider multiple factors, including the strength of the case against the defendant, the potential harms of granting the injunction, what other relief is available, and the public interest.  As part of this analysis, courts can and do tailor the relief they grant to what they conclude is necessary to remedy the harm. Nationwide injunctions may be necessary to stop nationwide unlawful conduct. And if an injunction was improperly granted, its target can appeal to have it overturned. 

To be clear, EFF doesn’t agree with every grant of nationwide relief. Courts sometimes get it wrong, often because they misinterpret the law they are asked to apply. If Congress wants to fix that kind of problem, it should draft specific legislation to reform or clarify specific laws. It should not, and cannot, rewrite our Constitutional system of checks and balances just because it doesn’t like some of the outcomes.

The move is part of a wholesale review of 56 FEMA programs to ensure they meet President Donald Trump's immigration enforcement efforts.

This is a truly fascinating paper: “Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography.” The basic idea is that AIs can act as trusted third parties:

Abstract: We often interact with untrusted parties. Prioritization of privacy can limit the effectiveness of these interactions, as achieving certain goals necessitates sharing private data. Traditionally, addressing this challenge has involved either seeking trusted intermediaries or constructing cryptographic protocols that restrict how much data is revealed, such as multi-party computations or zero-knowledge proofs. While significant advances have been made in scaling cryptographic approaches, they remain limited in terms of the size and complexity of applications they can be used for. In this paper, we argue that capable machine learning models can fulfill the role of a trusted third party, thus enabling secure computations for applications that were previously infeasible. In particular, we describe Trusted Capable Model Environments (TCMEs) as an alternative approach for scaling secure computation, where capable machine learning model(s) interact under input/output constraints, with explicit information flow control and explicit statelessness. This approach aims to achieve a balance between privacy and computational efficiency, enabling private inference where classical cryptographic solutions are currently infeasible. We describe a number of use cases that are enabled by TCME, and show that even some simple classic cryptographic problems can already be solved with TCME. Finally, we outline current limitations and discuss the path forward in implementing them...

The planned 25 percent tariff on imported automobiles is a gut punch for most electric vehicle makers, whose supply chains are rooted in China.

The EV company’s popularity has wilted in Europe and among left-leaning consumers.

Climate experts whose research is funded by federal grants hide, whisper and wait for their jobs to disappear.

A federal judge rejected oil companies' efforts to move the lawsuit out of the state court where it was first filed.

The rule would have required companies to provide climate information to investors. Its demise was expected under the Trump administration.

A House bill to bar environmental, social and governance investing also emerged this week.

Lawmakers are concerned about shifting funds from climate and pollution programs, but acknowledged a lack of options.

The Trump administration’s exit from the U.N.-led talks has created the “most challenging moment” for negotiations since their start in 1990, Liu Zhenmin said.

Overfishing compounds the problem, and geopolitical tensions make management difficult.

The French climate minister called for bolstering price-stabilization mechanisms and tweaking some elements of the current Emissions Trading System.

You’re an aerospace engineer on a tight timeline to develop a component for a rocket engine. No sweat, you think — you know the concepts by heart, and the model looks appropriate in CAD. But you inspect the 3D-printed part that you’ve outsourced for manufacturing, and something is wrong. The impeller blade angle is off, and the diameter is larger than the design intent. The vendor won’t get back to you. Suddenly you’re over budget. Something is leaking. Running the pump test rig, you’re not sure where that vibration is coming from.

Successfully navigating nightmares like this can make or break an engineer, but real-time problem-solving during assembly is something few undergraduates experience as part of their curriculum. Enter class 16.811 (Advanced Manufacturing for Aerospace Engineers), a new communication-intensive laboratory course that allows juniors and seniors to drive a full engineering cycle, gaining experience that mirrors the challenges they’ll face as practicing engineers.

In just 13 weeks, students design, build, and test a laboratory-scale electric turbopump, the type of pump used in liquid rocket propulsion systems to deliver fuel and oxidizer to the combustion chamber under high pressure. Teams of two or three students work through the entire production process while balancing budgets, documenting, and testing.

The course was developed and taught by Zachary Cordero, Esther and Harold E. Edgerton Associate Professor, and Zoltán Spakovszky, the T. Wilson Professor in Aeronautics, along with a team of teaching assistants (TAs), technical instructors, and communication experts. It ran for the first time last fall, open to students who had completed Unified Engineering, the foundational Course 16 curriculum covering the four disciplines at the core of aerospace engineering. It generated so much interest upon its announcement that spots were allocated via lottery.

“Sometimes it’s assumed that students will get hands-on experience through their extracurriculars, but they may not. Students in this class gain that experience through exposure to cutting-edge design and manufacturing tools, like metal 3D printing,” says Cordero. “They don’t just learn how to solve a problem set — they learn how to be an engineer.”

Training for a rapidly evolving field

The course was born out of feedback from participants at an annual workshop that Cordero organizes each summer addressing materials challenges in reusable rocket engines. Attendees representing industry, government, and academic sectors consistently emphasized the need for the next generation of engineers to be familiar with advanced engineering concepts, in addition to having strong fundamentals. Experience with new computational design tools and processes like additive manufacturing is becoming essential for success in the aerospace industry. “Our mission is to train, inspire, and motivate the next generation of aerospace engineers. We have to listen to what our industry partners want from engineers and adapt our curriculum to meet those needs,” says Cordero.

Spakovszky, Cordero, and the team built the course over two years of Independent Activities Period workshops, developing independent modules that teach concepts for constructing the turbopump. The first set of labs focuses on the impellers — the rotating bladed-disk component that draws fluid into the pump to pressurize it. The second lab breaks down the rotor system that supports the pump impeller, and the third covers integration of the rotor assembly into the casing and final testing.

Throughout the course, students receive instruction in technical communication and training on the full array of machine shop tools available in the Arthur and Linda Gelb Laboratory. Beyond learning the concepts and tools, the majority of the design and implementation is up to the students.

“They are pushed to learn how to learn on their own,” says Spakovszky. “The key differentiator here is that there is no solution. In other classes, you have a problem, and the instructor has the solution. This is open ended, and every team has a different design.” Project management is left up to each team, with instructors and TAs serving as resources, rather than leads. Each team works with vendors to help bring their designs to life. The students conducted their machinery analysis using the Agile Engineering Design System (AEDS) and Advanced Rotating Machine Dynamics (ARMD) software tools from Concepts NREC. Impellers were printed at the MIT SHED (Safety Health Environmental Discovery lab), with support from Tolga Durak, managing director of environment, health and safety, and by industry collaborators at Desktop Metal.

“A lot of the design questions we were working with don’t have firm answers,” says junior Danishell Destefano. “I learned a lot about how to read technical literature and compare design trade-offs to make my own decisions.”

On the floor

“Making things is really hard,” says Spakovszky. “In addition to manufacturing parts and components, the assembly of rotating machinery requires careful tolerancing of the part dimensions and precision manufacturing of the interfaces to meet design specification.”

At the core of the curriculum is the manufacturing process itself, with its myriad components posing a unique challenge for students who may not have experienced the kind of rapid design cycle that is becoming more and more common in the field. The course uses concurrent engineering as a methodology to emphasize the close connections between fundamental concepts, functional requirements, design, materials, and manufacturing.

Student teams document their lab results in written reports and give regular progress presentations. Lecturer Jessie Stickgold-Sarah instructed the class on professional communication. At the end of the semester, students walk away with the ability to not only create new things, but communicate about their creations.

“I really enjoyed working with this group of students,” says Stickgold-Sarah. “The main paper and presentations required students to express the reasoning using the design-build-test sequence, and to explain and justify their choices based on their technical understanding of core topics. They were incredibly hard-working and dedicated, and the papers and presentations they produced exceeded my expectations.”

The course culminates in a final presentation, where teams showcase their findings and get feedback from their MIT instructors and industry representatives — potential future colleagues and employers.

Whether or not students go directly into a career in rocket or jet propulsion, the breadth of skills they learn in class has applications across disciplines. “The biggest skill I’ve gained is time and project management. To build a pump in a semester is a pretty tough timeline challenge, and learning how to manage my time and work with a team has been a great soft skill to learn,” says Destafano.

The course drives home the reality that the manufacturing process can be just as important as the product. “I hope through this, they gain confidence to explore the unknown and deal with uncertainty in engineering systems,” says Cordero. “In the real world, things are leaking. Things aren’t as you initially anticipated or behaving as you thought they would behave. And the students had to react and respond. That's real life. It's kind of intuitive, kind of common sense, sure — but you can hone that skill, and develop confidence in that skill.”

Nature Climate Change, Published online: 28 March 2025; doi:10.1038/s41558-025-02308-y

Many climate models overestimate the snow amount in the Northern Hemisphere despite strong warming. Here the authors find that light snowfall and snow melting processes drive this mismatch and use these relationships to constrain future projections of snow water resources.

Every time you browse the web, you're being tracked. Most websites contain invisible tracking code that allows companies to collect and monetize data about your online activity. Many of those companies are data brokers, who sell your sensitive information to anyone willing to pay. That’s why EFF created Privacy Badger, a free, open-source browser extension used by millions to fight corporate surveillance and take back control of their data. 

Since we first released Privacy Badger in 2014, online tracking has only gotten more invasive and Privacy Badger has evolved to keep up. Whether this is your first time using it or you’ve had it installed since day one, here’s a primer on how Privacy Badger protects you.

Online Tracking Isn't Just Creepy—It’s Dangerous 

The rampant data collection, sharing, and selling fueled by online tracking has serious consequences. Fraudsters purchase data to identify elderly people susceptible to scams. Government agencies and law enforcement purchase people’s location data and web browsing records without a warrant. Data brokers help predatory companies target people in financial distress. And surveillance companies repackage data into government spy tools.

Once your data enters the data broker ecosystem, it’s nearly impossible to know who buys it and what they’re doing with it. Privacy Badger blocks online tracking to prevent your browsing data from being used against you. 

Privacy Badger Disrupts Surveillance Business Models

Online tracking is pervasive because it’s profitable. Tech companies earn enormous profits by targeting ads based on your online activity—a practice called “online behavioral advertising.” In fact, Big Tech giants like Google, Meta, and Amazon are among the top companies tracking you across the web. By automatically blocking their trackers, Privacy Badger makes it harder for Big Tech companies to profit from your personal information.

Online behavioral advertising has made surveillance the business model of the internet. Companies are incentivized to collect as much of our data as possible, then share it widely through ad networks with no oversight. This not only exposes our sensitive information to bad actors, but also fuels government surveillance. Ending surveillance-based advertising is essential for building a safer, more private web. 

While strong federal privacy legislation is the ideal solution—and one that we continue to advocate for—Privacy Badger gives you a way to take action today. 

Privacy Badger fights for a better web by incentivizing companies to respect your privacy. Privacy Badger sends the Global Privacy Control and Do Not Track signals to tell companies not to track you or share your data. If they ignore these signals, Privacy Badger will block them, whether they are advertisers or trackers of other kinds. By withholding your browsing data from advertisers, data brokers, and Big Tech companies, you can help make online surveillance less profitable. 

How Privacy Badger Protects You From Online Tracking

Whether you're looking to protect your sensitive information from data brokers or simply don’t want Big Tech monetizing your data, Privacy Badger is here to help.

Over the past decade, Privacy Badger has evolved to fight many different methods of online tracking. Here are some of the ways that Privacy Badger protects your data:

• Blocks Third-Party Trackers and Cookies: Privacy Badger stops tracking code from loading on sites that you visit. That prevents companies from collecting data about your online activity on sites that they don’t own. 
• Sends the GPC Signal to Opt Out of Data Sharing: Privacy Badger sends the Global Privacy Control (GPC) signal to opt out of websites selling or sharing your personal information. This signal is legally binding in some states, including California, Colorado, and Connecticut. 
• Stops Social Media Companies From Tracking You Through Embedded Content: Privacy Badger replaces page elements that track you but are potentially useful (like embedded tweets) with click-to-activate placeholders. Social media buttons, comments sections, and video players can send your data to other companies, even if you don’t click on them.
• Blocks Link Tracking on Google and Facebook: Privacy Badger blocks Google and Facebook’s attempts to follow you whenever you click a link on their websites. Google not only tracks the links you visit from Google Search, but also the links you click on platforms that feel more private, like Google Docs and Gmail. 
• Blocks Invasive “Fingerprinting” Trackers: Privacy Badger blocks trackers that try to identify you based on your browser's unique characteristics, a particularly problematic form of tracking called “fingerprinting.” 
• Automatically learns to block new trackers: Our Badger Swarm research project continuously discovers new trackers for Privacy Badger to block. Trackers are identified based on their behavior, not just human-curated blocklists.
• Disables Harmful Chrome Settings: Automatically disables Google Chrome settings that are bad for your privacy.
• Easy to Disable on Individual Sites While Maintaining Protections Everywhere Else: If blocking harmful trackers ends up breaking something on a website, you can disable Privacy Badger for that specific site while maintaining privacy protections everywhere else.

All of these privacy protections work automatically when you install Privacy Badger—there’s no setup required! And it turns out that when Privacy Badger blocks tracking, you’ll also see fewer ads and your pages will load faster. 

You can always check to see what Privacy Badger has done on the site you’re visiting by clicking on Privacy Badger’s icon in your browser toolbar.

Fight Corporate Surveillance by Spreading the Word About Privacy Badger

Privacy is a team sport. The more people who withhold their data from data brokers and Big Tech companies, the less profitable online surveillance becomes. If you haven’t already, visit privacybadger.org to install Privacy Badger on your web browser. And if you like Privacy Badger, tell your friends about how they can join us in fighting for a better web!

Install Privacy Badger

Metamaterials are artificially-structured materials with extraordinary properties not easily found in nature. With engineered three-dimensional (3D) geometries at the micro- and nanoscale, these architected materials achieve unique mechanical and physical properties with capabilities beyond those of conventional materials — and have emerged over the past decade as a promising way to engineering challenges where all other existing materials have lacked success.

Architected materials exhibit unique mechanical and functional properties, but their full potential remains untapped due to challenges in design, fabrication, and characterization. Improvements and scalability in this space could help transform a range of industries, from biomedical implants, sports equipment, automotive and aerospace, and energy and electronics.

“Advances in scalable fabrication, high-throughput testing, and AI-driven design optimization could revolutionize the mechanics and materials science disciplines, enabling smarter, more adaptive materials that redefine engineering and everyday technologies,” says Carlos Portela, the Robert N. Noyce Career Development Professor and assistant professor of mechanical engineering at MIT.

In a Perspective published this month in the journal Nature Materials, Portela and James Surjadi, a postdoc in mechanical engineering, discuss key hurdles, opportunities, and future applications in the field of mechanical metamaterials. The paper is titled “Enabling three-dimensional architected materials across length scales and timescales.”

“The future of the field requires innovation in fabricating these materials across length scales, from nano to macro, and progress in understanding them at a variety of time scales, from slow deformation to dynamic impact,” says Portela, adding that it also demands interdisciplinary collaboration.

A Perspective is a peer-reviewed content type that the journal uses to invite reflection or discussion on matters that may be speculative, controversial, or highly technical, and where the subject matter may not meet the criteria for a Review.

“We felt like our field, following substantial progress over the last decade, is still facing two bottlenecks: issues scaling up, and no knowledge or understanding of properties under dynamic conditions,” says Portela, discussing the decision to write the piece.

Portela and Surjadi’s paper summarizes state-of-the-art approaches and highlights existing knowledge gaps in material design, fabrication, and characterization. It also proposes a roadmap to accelerate the discovery of architected materials with programmable properties via the synergistic combination of high-throughput experimentation and computational efforts, toward leveraging emerging artificial intelligence and machine learning techniques for their design and optimization.

“High-throughput miniaturized experiments, non-contact characterization, and benchtop extreme-condition methods will generate rich datasets for the implementation of data-driven models, accelerating the optimization and discovery of metamaterials with unique properties,” says Surjadi.

The Portela Lab’s motto is “architected mechanics and materials across scales.” The Perspective aims to bridge the gap between fundamental research and real-world applications of next-generation architected materials, and it presents a vision the lab has been working toward for the past four years.

Six current MIT affiliates and 27 additional MIT alumni have been elected as fellows of the American Association for the Advancement of Science (AAAS). 

The 2024 class of AAAS Fellows includes 471 scientists, engineers, and innovators, spanning all 24 of AAAS disciplinary sections, who are being recognized for their scientifically and socially distinguished achievements.

Noubar Afeyan PhD ’87, life member of the MIT Corporation, was named a AAAS Fellow “for outstanding leadership in biotechnology, in particular mRNA therapeutics, and for advocacy for recognition of the contributions of immigrants to economic and scientific progress.” Afeyan is the founder and CEO of the venture creation company Flagship Pioneering, which has built over 100 science-based companies to transform human health and sustainability. He is also the chairman and cofounder of Moderna, which was awarded a 2024 National Medal of Technology and Innovation for the development of its Covid-19 vaccine. Afeyan earned his PhD in biochemical engineering at MIT in 1987 and was a senior lecturer at the MIT Sloan School of Management for 16 years, starting in 2000. Among other activities at the Institute, he serves on the advisory board of the MIT Abdul Latif Jameel Clinic for Machine Learning and delivered MIT’s 2024 Commencement address.

Cynthia Breazeal SM ’93, ScD ’00 is a professor of media arts and sciences at MIT, where she founded and directs the Personal Robots group in the MIT Media Lab. At MIT Open Learning, she is the MIT dean for digital learning, and in this role, she leverages her experience in emerging digital technologies and business, research, and strategic initiatives to lead Open Learning’s business and research and engagement units. She is also the director of the MIT-wide Initiative on Responsible AI for Social Empowerment and Education (raise.mit.edu). She co-founded the consumer social robotics company, Jibo, Inc., where she served as chief scientist and chief experience officer. She is recognized for distinguished contributions in the field of artificial intelligence education, particularly around the use of social robots, and learning at scale.

Alan Edelman PhD ’89 is an applied mathematics professor for the Department of Mathematics and leads the Applied Computing Group of the Computer Science and Artificial Intelligence Laboratory, the MIT Julia Lab. He is recognized as a 2024 AAAS fellow for distinguished contributions and outstanding breakthroughs in high-performance computing, linear algebra, random matrix theory, computational science, and in particular for the development of the Julia programming language. Edelman has been elected a fellow of five different societies — AMS, the Society for Industrial and Applied Mathematics, the Association for Computing Machinery, the Institute of Electrical and Electronics Engineers, and AAAS.

Robert B. Millard '73, life member and chairman emeritus of the MIT Corporation, was named a 2024 AAAS Fellow for outstanding contributions to the scientific community and U.S. higher education "through exemplary leadership service to such storied institutions as AAAS and MIT." Millard joined the MIT Corporation as a term member in 2003 and was elected a life member in 2013. He served on the Executive Committee for 10 years and on the Investment Company Management Board for seven years, including serving as its chair for the last four years. He served as a member of the Visiting Committees for Physics, Architecture, and Chemistry. In addition, Millard has served as a member of the Linguistics and Philosophy Visiting Committee, the Corporation Development Committee, and the Advisory Council for the Council for the Arts. In 2011, Millard received the Bronze Beaver Award, the MIT Alumni Association’s highest honor for distinguished service.

Jagadeesh S. Moodera is a senior research scientist in the Department of Physics. His research interests include experimental condensed matter physics: spin polarized tunneling and nano spintronics; exchange coupled ferromagnet/superconductor interface, triplet pairing, nonreciprocal current transport and memory toward superconducting spintronics for quantum technology; and topological insulators/superconductors, including Majorana bound state studies in metallic systems. His research in the area of spin polarized tunneling led to a breakthrough in observing tunnel magnetoresistance (TMR) at room temperature in magnetic tunnel junctions. This resulted in a huge surge in this area of research, currently one of the most active areas. TMR effect is used in all ultra-high-density magnetic data storage, as well as for the development of nonvolatile magnetic random access memory (MRAM) that is currently being advanced further in various electronic devices, including for neuromorphic computing architecture. For his leadership in spintronics, the discovery of TMR, the development of MRAM, and for mentoring the next generation of scientists, Moodera was named a 2024 AAAS Fellow. For his TMR discovery he was awarded the Oliver Buckley Prize (2009) by the American Physical Society (APS), named an American National Science Foundation Competitiveness and Innovation Fellow (2008-10), won IBM and TDK Research Awards (1995-98), and became a Fellow of APS (2000).

Noelle Eckley Selin, the director of the MIT Center for Sustainability Science and Strategy and a professor in the Institute for Data, Systems and Society and the Department of Earth, Atmospheric and Planetary Sciences, uses atmospheric chemistry modeling to inform decision-making strategies on air pollution, climate change, and toxic substances, including mercury and persistent organic pollutants. She has also published articles and book chapters on the interactions between science and policy in international environmental negotiations, in particular focusing on global efforts to regulate hazardous chemicals and persistent organic pollutants. She is named a 2024 AAAS Fellow for world-recognized leadership in modeling the impacts of air pollution on human health, in assessing the costs and benefits of related policies, and in integrating technology dynamics into sustainability science.

Additional MIT alumni honored as 2024 AAAS Fellows include: Danah Boyd SM ’02 (Media Arts and Sciences); Michael S. Branicky ScD ’95 (EECS); Jane P. Chang SM ’95, PhD ’98 (Chemical Engineering); Yong Chen SM '99 (Mathematics); Roger Nelson Clark PhD '80 (EAPS); Mark Stephen Daskin ’74, PhD ’78 (Civil and Environmental Engineering); Marla L. Dowell PhD ’94 (Physics); Raissa M. D’Souza PhD ’99 (Physics); Cynthia Joan Ebinger SM '86, PhD '88 (EAPS/WHOI); Thomas Henry Epps III ’98, SM ’99 (Chemical Engineering); Daniel Goldman ’94 (Physics); Kenneth Keiler PhD ’96 (Biology); Karen Jean Meech PhD '87 (EAPS); Christopher B. Murray PhD ’95 (Chemistry); Jason Nieh '89 (EECS); William Nordhaus PhD ’67 (Economics); Milica Radisic PhD '04 (Chemical Engineering); James G. Rheinwald PhD ’76 (Biology); Adina L. Roskies PhD ’04 (Philosophy); Linda Rothschild (Preiss) PhD '70 (Mathematics); Soni Lacefield Shimoda PhD '03 (Biology); Dawn Y. Sumner PhD ’95 (EAPS); Tina L. Tootle PhD ’04 (Biology); Karen Viskupic PhD '03 (EAPS); Brant M. Weinstein PhD ’92 (Biology); Chee Wei Wong SM ’01, ScD ’03 (Mechanical Engineering; and Fei Xu PhD ’95 (Brain and Cognitive Sciences).