AI Unpacked - Transforming Industries and Driving Innovation
For over 80 years, the digital revolution has redefined how we work, learn, and collaborate, reshaping societies and economies worldwide. Today, the rapid advancements in Artificial Intelligence and Machine Learning are accelerating this transformation, pushing the boundaries of what humans and machines can achieve together.
The 2025 MIT AI Conference will analyze the latest AI trends, groundbreaking developments, and their profound implications for the future of knowledge, work, skills, and intelligence. Key themes include:
The conference will also feature transformative startups emerging from MIT’s labs, showcasing cutting-edge technologies poised to redefine industries.
Dr. Srinivasan is a distinguished scientist who received her PhD in Microbiology from The Ohio State University in 2004, where she contributed to the discovery of the 22nd amino acid, Pyrrolysine (2002). She first came to MIT as an NIH Postdoctoral Fellow in Prof. Tom Rajbhandary’s lab, where her research focused on understanding protein synthesis mechanisms in Archaea.
Dr. Srinivasan subsequently moved into the business development and technology licensing space, serving in MIT’s Technology Licensing Office, where she helped commercialize technologies in medical devices and alternative energies. She then moved to UMass Medical School’s Office of Technology Management in 2009 and to Emory University in Atlanta in 2014 as the Director of Public and Private Partnerships for the Woodruff Health Sciences Center. In 2019, Dr. Srinivasan joined Emory’s Office of Corporate Relations as Executive Director, and in 2021, she led the Office of Corporate and Foundation Relations.
Dean, MIT Schwarzman College of Computing Professor, MIT Department of Electrical Engineering and Computer Science (EECS)
Daniel Huttenlocher is the inaugural dean of the MIT Schwarzman College of Computing and is the Henry Ellis Warren (1894) Professor of Electrical Engineering and Computer Science.
Previously he helped found Cornell Tech, the digital technology-oriented graduate school created by Cornell University in New York City, and served as its first Dean and Vice Provost.
His research and teaching have been recognized by a number of awards including ACM Fellow and CASE Professor of the Year. He has a mix of academic and industry background, having been a Computer Science faculty member at Cornell, researcher and manager at the Xerox Palo Alto Research Center (PARC), and CTO of a fintech startup.
Huttenlocher is an internationally recognized researcher in computer vision and the analysis of social media. His book, “The Age of AI: And Our Human Future,” co-authored with Henry Kissinger and Eric Schmidt, was published by Little, Brown in November 2021. He served as a member and as the chair of the board of the John D. and Catherine T. MacArthur Foundation, and currently serves as a member of the boards of Corning Inc. and Amazon.com.
He received his bachelor’s degree from the University of Michigan, and master’s and doctorate from MIT.
In The Age of AI, we consider how AI will change our relationships with knowledge, politics, and the societies in which we live. These changes are becoming more prominent with every passing moment, and this session endeavors to find the path that best embraces the change for the benefit of business and society.
Daniel (1972) and Gail Rubinfeld Professor Margaret MacVicar Faculty Fellow MIT Department of Economics
David Autor is the Daniel (1972) and Gail Rubinfeld Professor in the MIT Department of Economics, co-director of the NBER Labor Studies Program and the MIT Shaping the Future of Work Initiative. His scholarship explores the labor-market impacts of technological change and globalization on job polarization, skill demands, earnings levels and inequality, and electoral outcomes.
Autor has received numerous awards for his scholarship—the National Science Foundation CAREER Award, an Alfred P. Sloan Foundation Fellowship, the Sherwin Rosen Prize for outstanding contributions to the field of Labor Economics, the Andrew Carnegie Fellowship in 2019, the Society for Progress Medal in 2021—and for his teaching, including the MIT MacVicar Faculty Fellowship. In 2020, Autor received the Heinz 25th Special Recognition Award from the Heinz Family Foundation for his work “transforming our understanding of how globalization and technological change are impacting jobs and earning prospects for American workers.” In 2023, Autor was selected as one of two researchers across all scientific fields a NOMIS Distinguished Scientist. Autor was one of five senior scholars selected by the Schmidt Sciences Foundation as an AI2050 Senior Fellow in 2024.
The Economist magazine labeled Autor in 2019 as “The academic voice of the American worker.” Later that same year, and with equal or greater justification, he was christened “Twerpy MIT Economist” by John Oliver of Last Week Tonight in a segment on automation and employment.
Autor is an elected Fellow of the Econometrics Society, the Society of Labor Economists, and the American Academy of Arts and Sciences, and a Faculty Research Associate of the National Bureau of Economic Research and the Abdul Latif Jameel Poverty Action Lab. He is co-director of the NBER Labor Studies Program, Co-Director of the MIT School Effectiveness and Inequality Initiative, and Scientific Advisor to the NBER Disability Research Center.
His teaching awards include the MIT MacVicar Faculty Fellowship for contributions to undergraduate education, the James A. and Ruth Levitan Award for excellence in teaching, the Undergraduate Economic Association Teaching Award, and the Faculty Appreciation Award from the MIT TPP program.
Autor earned a B.A. in Psychology from Tufts University and a Ph.D. in Public Policy from Harvard’s Kennedy School of Government in 1999. Prior to graduate study, he spent three years directing computer skills education for economically disadvantaged children and adults in San Francisco and South Africa. Autor is the captain of the MIT Economics hockey team, which is reputed to be one of the most highly cited teams in the MIT intramural league.
Will recent advances in AI complement human expertise, thereby increasing its value, or render it increasingly unnecessary, thus reducing its value (even if jobs are not in net eliminated)? Prof Autor will frame this question through the lens of three technological revolutions of the last two centuries: the Industrial Revolution, the Computer Revolution, and the AI Revolution. In each, the types of expertise rewarded changed substantially, with vastly uneven consequences for workers in different occupations and possessing different education levels. These forces will play out differently in the AI era than in preceding decades. While the future is not a forecasting exercise -- it's a design problem -- Prof Autor will discuss the opportunities that AI opens for the labor market, as well as some of the risks it poses.
Manager, Business Development and Marketing, MIT Professional Education
Michael Schrage is a research fellow with the MIT Sloan School of Management's Initiative on the Digital Economy. His research, writing, and advisory work focuses on the behavioral economics of models, prototypes, and metrics as strategic resources for managing innovation risk and opportunity. He is author of the award-winning book The Innovator’s Hypothesis (MIT Press, 2014), Who Do You Want Your Customers to Become? (Harvard Business Review Press, 2012), and Serious Play (Harvard Business Review Press, 2000). His latest book, Recommendation Engines, was published in September 2020 by MIT Press as part of its Essential Knowledge series. He's done consulting and advisory work for Microsoft, Procter & Gamble, British Telecom, BP, Siemens, Embraer, Google, iRise, the Office of Net Assessment, and other organizations
Schrage has run design workshops and executive education programs on innovation, experimentation, and strategic measurement for organizations all over the world and is currently pioneering work in selvesware technologies designed to augment aspects, attributes, and talents of productive individuals. He is particularly interested in the future co-evolution of expertise, advice, and human agency as technologies become smarter than the people using them.
Professor, MIT Department of Brain and Cognitive Sciences
Josh Tenenbaum is a Professor of Computational Cognitive Science in the Department of Brain and Cognitive Sciences at MIT, a principal investigator at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), and a thrust leader in the Center for Brains, Minds, and Machines (CBMM). His research centers on perception, learning, and common-sense reasoning in humans and machines, with the twin goals of better understanding human intelligence in computational terms and building more human-like intelligence in machines. The machine learning and artificial intelligence algorithms developed by his group are currently used by hundreds of other science and engineering groups around the world.
Tenenbaum received his PhD from MIT in 1999 and was an Assistant Professor at Stanford University from 1999 to 2002 before returning to MIT. His papers have received awards at the Cognitive Science (CogSci), Computer Vision and Pattern Recognition (CVPR), Neural Information Processing Systems (NIPS), and Uncertainty in Artificial Intelligence (UAI) conferences, the International Conference on Learning and Development (ICDL) and the International Joint Conference on Artificial Intelligence (IJCAI). He has given invited keynote talks at all of the major machine learning and artificial conferences, as well as the main meetings of the Cognitive Science Society, the Cognitive Development Society, and the Society for Mathematical Psychology, and held distinguished lectureships at Stanford University, the University of Amsterdam, McGill University, the University of Pennsylvania, the University of California, San Diego, and the University of Arizona. He is the recipient of the Early Investigator Award from the Society of Experimental Psychologists, the Distinguished Scientific Award for Early Career Contribution to Psychology from the American Psychological Association, and the Troland Research Award from the National Academy of Sciences, and is a fellow of the Society of Experimental Psychologists and the Cognitive Science Society.
Professor, MIT Department of Linguistics and Philosophy
Caspar Hare is a professor of philosophy in the Department of Linguistics and Philosophy. Along with Nikos Trichakis, Hare is the associate dean for Social and Ethical Responsibilities of Computing (SERC) in the MIT Schwarzman College of Computing. Hare and Trichakis work together to create multidisciplinary connections on campus and to weave social, ethical, and policy considerations into the teaching, research, and implementation of computing.
A member of the MIT faculty since 2003, Hare’s main interests are in ethics, metaphysics, and epistemology. The general theme of his recent work has been to bring ideas about practical rationality and metaphysics to bear on issues in normative ethics and epistemology. He is the author of two books: “On Myself, and Other, Less Important Subjects” (Princeton University Press 2009), about the metaphysics of perspective, and “The Limits of Kindness” (Oxford University Press 2013), about normative ethics.
Dean, MIT School of Humanities, Arts, and Social Sciences
Agustin Rayo is Professor of Philosophy and Dean of MIT's School of Humanities, Arts, and Social Sciences. His research lies at the intersection of the philosophy of logic and the philosophy of language. He is the author of numerous articles and two books: “The Construction of Logical Space” (OUP, 2013) and “On the Brink of Paradox” (MIT Press, 2019), which won the 2020 PROSE Award for best textbook in the humanities.
Computer Science Head, MIT Department of Electrical Engineering and Computer Science
Sam Madden is a professor of EECS and principal investigator in CSAIL at MIT. His research interests are in database systems, focusing on database analytics and query processing, ranging from clouds to sensors to modern high-performance server architectures. A member of the MIT faculty since 2004, he was recognized as the inaugural College of Computing Distinguished Professor of Computing in 2020 and currently serves as the head of Computer Science in the EECS department. He also co-directs the Data Systems for AI Lab initiative and the Data Systems Group, investigating issues related to systems and algorithms for data, focusing on applying new methodologies for processing data, including applying machine learning methods to data systems and engineering data systems for applying machine learning at scale. He was named one of MIT Technology Review's Top 35 Under 35 in 2005 and an ACM Fellow in 2020 and is the recipient of several awards, including an NSF CAREER Award, a Sloan Foundation Fellowship, the ACM SIGMOD Edgar F. Codd Innovations Award for lifetime accomplishments in the area of data management, and “test of time” awards from VLDB, SIGMOD, CIDR, SIGMOBILE, and SenSys. He is also the co-founder and Chief Scientist at Cambridge Mobile Telematics, which develops technology to make roads safer and drivers better.
Knowledge is core to the human experience. Over millennia, questions about how humans acquire, learn, understand, dispute and share knowledge have animated scientists, philosophers, artists, engineer,s and politicians. Our increasingly digital society is built on crystalized, and often contested, knowledge – from history and law to software and social networks – crafted at a human scale by humans for humans. However, new forms of machine intelligence are emerging – ones that collect, represent, reason, and engineer with knowledge in very non-human ways and at very non-human scales, This panel will bring together experts from multiple disciplines to discuss the profound impact of this emerging partnership.
Patrick J. McGovern (1959) Professor, MIT Sloan School of Management Faculty Co-Director, MIT Generative AI Impact Consortium
Vivek is interested in the development of new methodologies for large scale dynamic optimization and applications in revenue management, finance, marketing and healthcare. He received his Ph.D. in Electrical Engineering from Stanford University in 2007 and has been at MIT since, where he is the Robert N. Noyce Professor of Management. Vivek is a recipient of an IEEE Region 6 Undergraduate Student Paper Prize (2002), an INFORMS MSOM Student Paper Prize (2006), an MIT Solomon Buchsbaum Award (2008), an INFORMS JFIG paper prize twice (2009, 2011), the NSF CAREER award (2011), MIT Sloan’s Outstanding Teacher award (2013), and the INFORMS Simulation Society Best Publication Award (2014). Outside of academia, he contributed to the design of the algorithmic trading strategies of GMO's (a USD 100B + money manager) first high frequency venture and in 2014 co-founded a retail technology company.
The MIT Generative AI Impact Consortium aims to harness the transformative power of GenAI for impact across a range of domains: life sciences, health, material science, climate and sustainability, linguistics, manufacturing, finance, business, media, education, and more. This presentation will provide an overview of the consortium's mission, key objectives, and collaborative efforts with industry leaders and MIT researchers. Attendees will gain insights into the consortium's focus on advancing generative AI applications across diverse sectors, addressing societal challenges, and shaping the future of AI technology.
Catarina has been working with the Cambridge/Boston startup ecosystem for over 10 years and joined Corporate Relations with a solid network in the innovation and entrepreneurial community. Prior to MIT, she was part of the team that designed and launched the startup accelerator IUL MIT Portugal, which was later rebranded as Building Global Innovators. She was based in Lisbon and worked in direct relation with the Cambridge team. She held positions including Operations Coordinator, Program Manager, and Business Developer. The accelerator soon achieved steady growth in large part due to the partnerships that Catarina led with regional and global startup ecosystems. After that, she worked at NECEC, leading a program that connects cleantech startups and industry. In this role, she developed and built a pipeline of startups and forged strong relationships with both domestic and European companies. She has also held positions in Portugal and France, including at Saboaria e Perfumaria Confiança and L’Oréal as Technical Director and Pharmacist. Catarina earned her bachelor's in chemistry and pharmaceutical sciences in Portugal. She went on to earn her Master of Engineering for Health and Medicines in France.
Founder & CEO, Eva
Murat Onen is the founder and CEO at Eva, a company developing next-generation AI training processors powered by a breakthrough class of semiconductors. Dr. Onen has received his MSc. and PhD. degrees from MIT in EECS, where his doctoral dissertation received the prestigious MIT Best PhD Thesis in Electrical Engineering Award. By leveraging an unprecedentedly deep hardware-software codesign approach, the company is now building 1.65 ExaFLOPS Outcomputers™—single-rack μ-datacenters—offering 72x higher throughput-per-TCO compared to NVIDIA B100-equipped servers. His research spans semiconductor device engineering, nanofabrication, mixed-signal processor architectures, and novel AI algorithms, resulting in 17 publications and 16 patents to date. Currently, he is leading Eva, where the company is building the deepest technology stack ever attempted to enable advanced AI applications that are far beyond current reach.
Co-Founder & CEO, Perygee
Mollie Breen is the Co-founder & CEO of Perygee, an AI-native digital enterprise fabric that ties together siloed systems with powerful automation & interfaces so enterprise teams can answer any question about their environment and automate any workflow—in minutes not months. Before co-founding Perygee, she was a mathematician at the NSA, leading initiatives at the intersection of national security and AI. Mollie is a recognized thought leader in IT & security automation, advising IT & security teams as a faculty member with IANS Research. Mollie is a graduate of Duke University and Harvard Business School.
Founder & CEO, SafeMode Mobility
Ido Levy, Founder and CEO of SafeMode Mobility, is an award-winning entrepreneur recognized for his work in using Behavioral Science and Artificial Intelligence to develop cutting-edge solutions for the transportation industry, especially the notable SafeMode driver engagement platform. He has received several accolades, including being named a "top young entrepreneur" by the European Union, "Rising Star of the Year -under 30" by TU-Automotive, "Inspiration of the Year under 30" by Informa Tech, and winning the SAE WCX Connected Cars Challenge. Prior to starting SafeMode, Ido served as an officer in a counter-terrorism unit in the military.
Co-Founder, Tinfoil
Sacha recently completed his PhD from MIT CSAIL where his research was focused on cryptography and privacy-preserving systems. Sacha cofounded Tinfoil to tackle the increasing privacy and security issues associated with AI applications.
Co-founder & CEO, getIntro
Jeff Feldgoise is a Co-founder and CEO of Assure AI, a company that is helping vendors grow their revenue in the healthcare market more quickly and efficiently. Previously, he led software engineering and data science teams in the health tech industry, building AI products that reached over 100,000 patients and 1,000 clinicians in more than 60 countries. Earlier in his career, Jeff was a product leader in fintech, where he launched ground-breaking online trading platforms and robo-advisory services for millions of individual investors. Jeff holds both undergraduate and graduate degrees from MIT, where he studied architecture and computer science, blending design with engineering to create user-focused solutions.
Founder & CEO, Vocadian
Yujie Wang is an AI product leader, Human-Computer Interaction researcher, and a serial entrepreneur. He has a background in Human-Computer Interaction from MIT and Harvard, focusing on wearable computing, Brain-Computer Interfaces, voice/digital biomarkers, and sleep/circadian science. Yujie has research experience at MIT Media Lab and Harvard Medical School, and professional experience building category-defining products across diverse industries, including preventative healthcare, smart home, supply chain, precision agriculture, and autonomous driving. His expertise spans PM, engineering, and UX, honed at global innovators like Philips Healthcare, IKEA Home Smart, Maersk, and FaunaPhotonics. Yujie takes innovation from ideas to commercialization. He shapes human relationships with machines and the environment, building products that cultivate empathy, trust, and care.
CEO, Displaid
Dr. Lorenzo Benedetti, 30, was born in a small village in the center of Italy. In 2013 he moved to Milan, where he currently lives, to study mechanical and management engineering at Politecnico. Following graduation, he obtained a PhD working between Politecnico and MIT, with a focus on bridge monitoring. Since 2023, Lorenzo is the CEO of Displaid, a startup born to guarantee the safety and efficiency of transportation networks through a scalable bridge monitoring solution.
Co-Founder Unbox AI
Rickard Brüel Gabrielsson is an AI researcher from Stanford and MIT, a lecturer for MIT’s Foundation Models & Generative AI course, and co-founder of Unbox AI.
CEO & Co-Founder, Gaia AI
Peter McHale is the CEO and co-founder of Gaia AI, an MIT spinout company applying modern data and AI technologies for the timber and logging industry. He has technical master's degrees from Carnegie Mellon University (in computer engineering) as well as the University of Michigan (in robotics + AI). He received his MBA from MIT's Sloan School of Business. He spent his early career building perception AI for Ford Motor Company and then helped build the foundational perception AI technology at two autonomous vehicle companies that both grew to be worth over $1B: Argo AI and May Mobility.
CEO, Tristar AI
Growing up, Salem Karani spent years helping operate his family’s plastics manufacturing business in Houston, Texas. He watched his father endure sleepless nights fixing problems at the factory—issues that could have been prevented with automation or real-time alerts. Witnessing firsthand the toll this took on him, Karani was inspired to create Tristar AI, with a mission to help his father—and the manufacturing industry as a whole—save valuable time, money, and labor. Karani’s journey into this field led him to Harvard, where he studied computer vision. In 2022, while conducting research at MIT, he began developing the foundation for Tristar AI, focusing on how machine learning and computer vision could revolutionize quality control and manufacturing efficiency. At Tristar AI, the team believes in the transformative capabilities of computer vision technology to provide real-time insights for workers and factory managers. By monitoring quality and tracking compliance, their solutions create safer, more efficient workplaces while preventing costly mistakes before they happen. The goal: to empower people to work smarter, not harder.
Donner Professor, MIT Department of Electrical Engineering and Computer Science (EECS)
Jesus A. del Alamo is the Donner Professor and Professor of Electrical Engineering at Massachusetts Institute of Technology. He obtained a Telecommunications Engineer degree from the Polytechnic University of Madrid and MS and PhD degrees in Electrical Engineering from Stanford University. From 1985 to 1988 he was with Nippon Telegraph and Telephone LSI Laboratories in Japan and since 1988 he has been with the Department of Electrical Engineering and Computer Science of Massachusetts Institute of Technology. From 2013 until 2019, he served as Director of the Microsystems Technology Laboratories at MIT. His current research interests are focused on nanoelectronics based on compound semiconductors and ultra-wide bandgap semiconductors.
Prof. del Alamo was an NSF Presidential Young Investigator. He is a member of the Royal Spanish Academy of Engineering and Fellow of the Institute of Electrical and Electronics Engineers, the American Physical Society and the Materials Research Society. He is the recipient of the Intel Outstanding Researcher Award in Emerging Research Devices, the Semiconductor Research Corporation Technical Excellence Award, the IEEE Electron Devices Society Education Award, the University Researcher Award by Semiconductor Industry Association and Semiconductor Research Corporation, the IPRM Award and the IEEE Cledo Brunetti Award. He currently serves as Editor-in-Chief of IEEE Electron Device Letters. He is the author of “Integrated Microelectronic Devices: Physics and Modeling” (Pearson 2017, 880 pages), a rigorous and up to date description of transistors and other contemporary microelectronic devices.
AI’s rapid progress has been driven by continuous innovation in computing hardware. Professor del Alamo will discuss the latest advancements in semiconductor technology and specialized AI chips, highlighting key trends in efficiency, scalability, and computing power. He will also explore what lies ahead—from novel materials and architectures to the geopolitical forces shaping AI chip development.
Professor, MIT Department of Electrical Engineering and Computer Science Associate Director and COO, MIT Computer Science & Artificial Intelligence Laboratory
Armando Solar-Lezama is a Professor in the department of Electrical Engineering and Computer Science at MIT and is also Associate Director and COO of the Computer Science and Artificial Intelligence lab. He also leads the NSF Funded Expeditions project "Understanding the World Through Code", a large multi-institution effort that works on applying neurosymbolic reasoning techniques to support scientific discovery.
AI is not just transforming industries—it’s revolutionizing software development. From AI-assisted coding to automated testing and lifecycle management, new tools are enhancing productivity, quality, and security. The speaker will explore the impact of AI-driven programming, the evolving role of software engineers, and the challenges of ensuring control, reliability, and trust in AI-generated code.
Vice Provost for Open Learning, MIT Sloan School of Management Associate Dean for Business Analytics, MIT Sloan School of Management
Dimitris Bertsimas is the current Vice Provost for Open Learning, the Associate Dean of Business Analytics, the Boeing Professor of Operations Research, and the faculty director of the Master of Business Analytics program at MIT, where he has been a faculty member since 1988. His research focuses on optimization, machine learning, and applied probability, with applications in healthcare, finance, operations management, and transportation. He has authored over 300 scientific papers and seven graduate-level textbooks.
As AI reshapes industries and job markets, how can we ensure that individuals—from professionals in developed economies to workers in emerging markets—are equipped for an AI-powered future? Dr. Bertsimas, Vice Provost for MIT Open Learning, will outline MIT’s vision for large-scale AI education, exploring new models of upskilling and the strategies needed to prepare one billion people for the AI-driven workforce.
Associate Professor, MIT Department of Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES)
Dr. Marzyeh Ghassemi is an Associate Professor at MIT in Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES), and a Vector Institute faculty member holding a Canadian CIFAR AI Chair and Canada Research Chair. She holds MIT affiliations with the Jameel Clinic and CSAIL.
Professor Ghassemi holds a Herman L. F. von Helmholtz Career Development Professorship and was named a CIFAR Azrieli Global Scholar and one of MIT Tech Review’s 35 Innovators Under 35. Previously, she was a Visiting Researcher with Alphabet’s Verily and an Assistant Professor at the University of Toronto. Prior to her PhD in Computer Science at MIT, she received an MSc. degree in biomedical engineering from Oxford University as a Marshall Scholar and B.S. degrees in computer science and electrical engineering as a Goldwater Scholar at New Mexico State University.
Professor Ghassemi has previously served as a NeurIPS Workshop Co-Chair and General Chair for the ACM Conference on Health, Inference and Learning (CHIL). She also founded the non-profit Association for Health Learning and Inference. Professor Ghassemi has published across computer science and clinical venues, including NeurIPS, KDD, AAAI, MLHC, JAMIA, JMIR, JMLR, AMIA-CRI, Nature Medicine, Nature Translational Psychiatry, and Critical Care.
Machine learning in health has made impressive progress in recent years, powered by an increasing availability of health-related data and high-capacity models. While many models in health now perform at, or above, humans in a range of tasks across the human lifespan, models also learn societal biases and may replicate or expand them. In this talk, Dr. Marzyeh Ghassemi will focus on the need for machine learning researchers and model developers to create robust models that can be ethically deployed in health settings, and beyond. Dr. Ghassemi's talk will span issues in data collection, outcome definition, algorithm development, and deployment considerations.
Germeshausen Professor and Professor of Media Technology, MIT Media Lab Head, Fluid Interfaces Research Group
Pattie Maes is the Germeshausen Professor of Media Arts and Sciences at the MIT Media Lab. She runs the Fluid Interfaces research group, which does research at the intersection of Human Computer Interaction and Artificial Intelligence with a focus on applications in health, wellbeing and learning. Maes is also a faculty member in MIT's center for Neuro-Biological Engineering. She is particularly interested in the topic of cognitive enhancement, or how wearable, immersive and brain-computer interface systems can actively assist people with issues such as memory, attention, learning, decision making, communication, wellbeing, and sleep.
Maes is the editor of four books, and is an editorial board member and reviewer for numerous professional journals and conferences. She has received several awards: Netguru selected her for "Hidden Heroes: the people who shaped technology (2022), Time Magazine has included several of her designs in its annual list of inventions of the year; AAAI gave her the "classic paper 2012" prize, awarded to the most influential AI paper of the year, Fast Company named her one of 50 most influential designers (2011); Newsweek picked her as one of the "100 Americans to watch for" in the year 2000; TIME Digital selected her as a member of the “Cyber Elite,” the top 50 technological pioneers of the high-tech world; the World Economic Forum honored her with the title "Global Leader for Tomorrow"; Ars Electronica awarded her the 1995 World Wide Web category prize; and in 2000 she was recognized with the "Lifetime Achievement Award" by the Massachusetts Interactive Media Council. She also received honorary doctorates from the Vrije Universiteit Brussel in Belgium and Open Universiteit, Netherlands, and has given several TED talks.
In addition to her academic endeavors, Maes has been an active entrepreneur as co-founder of several venture-backed companies, including Firefly Networks (sold to Microsoft), Open Ratings (sold to Dun & Bradstreet) and Tulip Co (privately held). She is an advisor to several early stage companies, including Earable, Inc, and Spatial, Inc. Prior to joining the Media Lab, Maes was a visiting professor and a research scientist at the MIT Artificial Intelligence Lab. She holds a bachelor's degree in computer science and a PhD in artificial intelligence from the Vrije Universiteit Brussel in Belgium.
AI is not just an engineering challenge, it is also a human design problem. For AI to live up to its lofty expectations and benefit humankind, it is important that we not just optimize AI itself and make it more accurate, efficient, and safe, but that we also understand how people respond to interaction with AI and how we best design that interaction to achieve optimal short and long term outcomes.
Computer Science, Economics, and Data Science Major, MIT Social and Ethical Responsibilities of Computing (SERC) Scholar, MIT Schwarzman College of Computing
Audrey Lorvo is an MIT senior studying Computer Science, Economics, and Data Science, with a concentration in International Development. A researcher and advocate for responsible AI development, her work focuses on AI risk management, governance, and policy. She is a Research Assistant at MIT FutureTech, where she contributes to the AI Risk Repository and the AI Risk Index, curating a database of best-practice AI risk mitigation strategies for organizations to address AI risks relevant to them. As a Social and Ethical Responsibilities of Computing Scholar at the MIT Schwarzman College of Computing, she examines the societal and economic implications of AI, with a particular focus on AI automating its own research and development.
Passionate about interdisciplinary problem-solving, Audrey serves as President of the MIT Undergraduate Economics Association, representing the Economics student body. Her previous research spans economic policy, urban planning, and data science, including contributions to the Organisation for Economic Co-operation and Development (OECD) on place-based policies and analyzing AI’s role in global innovation.
Audrey is French-American and brings a unique perspective from having grown up in France, Argentina, Japan, Brazil, Mexico, and the U.S. Fluent in French, English, Spanish, and Portuguese, she has engaged in international research initiatives in Chile, France, and Madagascar.
With a background in computer science, economics, and data science, Audrey is dedicated to exploring how AI can be developed safely and effectively, ensuring that technological progress benefits society while mitigating risks. She is excited to contribute to AI safety and governance research in the U.S., Europe, and beyond, helping organizations navigate the complexities of AI’s evolving landscape.
As AI permeates every sector of the economy, addressing and mitigating its associated risks becomes increasingly crucial. For firms developing and deploying AI, the institutions governing its use, and individuals navigating this technological shift, identifying and managing the most critical risks remains a significant challenge.
This talk will first explore how MIT FutureTech’s AI Risk Repository and Risk Index provide a comprehensive framework to help organizations prioritize AI risks and implement effective mitigation strategies. Next, Lorvo will highlight the perspective of the MIT AI Alignment Club, featuring student voices and showcasing various avenues of student-led research. By examining why so many MIT students are pivoting their careers toward AI safety, we will illustrate how the next generation of researchers and leaders is working to shape a more secure and resilient AI-driven future.
Finally, Lorvo will propose ways to bridge the gap between students, research centers, policymakers, and businesses to build a path toward safer AI systems.
Jerry McAfee Professor of Engineering, MIT Department of Civil and Environmental Engineering and MIT Department of Mechanical Engineering
Dr. Markus J. Buehler, Jerry McAfee Professor of Engineering at MIT, is a leading researcher in computational modeling across domains, from materials to biology to physics. Markus' expertise bridges AI to multi scale materials modeling. He recently co-developed a method that uses artificial intelligence to generate new protein designs with specific strengths, mimicking natural materials like silk. This approach, which uses computer simulations for testing, allows the creation of proteins with desired mechanical properties, such as strength and flexibility, beyond what is naturally available. Markus earned a Ph.D. at the Max Planck Institute for Metals Research at the University of Stuttgart and held post-doctoral appointments at both Caltech and MIT. Buehler has received many awards, including the Feynman Prize, the Drucker Medal, and the Washington Award. He is a member of the National Academy of Engineering.
AI is evolving beyond pattern recognition into a tool for reasoning, discovery, and scientific insight. This talk explores how new AI architectures, including Reinforcement Learning (RL) and Graph Isomorphism Networks (GIN), enabling us to build powerful expressive AI models that move beyond memorization and into structural reasoning. By blending physics-driven models with generative AI, integrating biologically-inspired neural structures, and leveraging multi-agent systems that mirror collective intelligence in nature, we unlock new frontiers in scientific discovery. Case studies will highlight breakthroughs in materials science, demonstrating AI-driven advances with real-world applications in medicine, food, and agriculture. These developments showcase AI's potential not just as a tool for analysis but as an engine for reasoning, adaptation, and discovery, fundamentally reshaping our understanding of complex systems.
Principal Investigator, MIT Probabilistic Computing Project
Vikash Mansinghka is a Principal Research Scientist at MIT, where he leads the Probabilistic Computing Project, and CEO of CHI FRO, a non-profit collaborating with MIT to scale rational Al and reverse-engineer the brain. He has co-founded multiple VC-backed startups, including Prior Knowledge (acquired by Salesforce in 2012) and Empirical Systems (acquired by Tableau in 2018). His research has won awards from the top conferences in computer vision, cognitive science, and programming languages.
Vikash holds S.B. degrees in Mathematics and in Computer Science from MIT, as well as an M.Eng. in Computer Science and a PhD in Computation. As a PhD student, he held graduate fellowships from the National Science Foundation and MIT’s Lincoln Laboratory, and his PhD dissertation on natively probabilistic computation won the MIT George M. Sprowls dissertation award. He served on DARPA’s Information Science and Technology advisory board from 2010-2012, currently serves on the editorial board for the Journal of Machine Learning Research, and co-founded the International Conference on Probabilistic Programming.
What kinds of computations give rise to human intelligence? And how can they be scaled in silicon? A great deal of enthusiasm has been focused on answering these questions by building increasingly large deep learning systems. This talk shows how an alternate scaling route, based on probabilistic programs and spiking probabilistic hardware, integrating the best of deep learning, is being used to make new kinds of generative software models and agents that are engineered — not learned from data! — and guaranteed by design to be safe, assistive, and rational. It will also show evidence that this kind of AI better explains the computations unfolding in our own minds and brains than today’s artificial neural networks, and how we can apply this understanding to deliver computational intelligence that is much easier for us to talk to, teach, and justifiably trust.
Drew Houston (2005) Career Development Professor and Assistant Professor of Information Technology, MIT Sloan School of Management
Manish Raghavan is the Drew Houston (2005) Career Development Professor at the MIT Sloan School of Management and Department of Electrical Engineering and Computer Science. Before that, he was a postdoctoral fellow at the Harvard Center for Research on Computation and Society (CRCS). His research centers on the societal impacts of algorithmic decision-making.
AI and related technologies have far-reaching implications for society. In this talk, we bring together perspectives from computer science, economics, and the law to build a comprehensive understanding of how AI impacts society and how we can ensure that the impacts are positive. We present case studies in medical decision-making, employment, and creative competition.