Five MIT college members and two additional alumni were recently recognized for their outstanding achievements in science and technology.
Conceived and co-chaired by Eric Schmidt and James Manyika, AI 2050 is a philanthropic initiative designed to address In their thought-provoking examination, each researcher will grapple with the pivotal driving question of AI2050: “What would happen if it were already 2050?” The advent of artificial intelligence has had a profoundly positive impact on modern society. What occurred? We resolved pivotal challenges by adopting creative alternatives and seized opportunities to guarantee this outcome, thereby.
The 2022 cohort of MIT-affiliated AI2050 Fellows comprises:
The renowned economist and professor at MIT’s Department of Economics, and co-director of both the MIT Shaping the Future of Work Initiative and the National Bureau of Economic Research’s Labor Research Program, has been appointed a 2024 AI2050 senior fellow. His research delves into the far-reaching consequences of technological advancements and globalization on job polarization, skill requirements, pay scales, income disparities, and ultimately, electoral results. The author’s AI 2050 venture will utilize real-time insights into AI adoption to demonstrate the synergies between cutting-edge tools and human aptitudes in reshaping job opportunities and compensation structures.
The work will provide a comprehensible framework for entrepreneurs, technologists, and policymakers seeking to understand, concretely, how AI can enhance human interaction. The author has acquired several prestigious awards and honors, including a National Science Foundation CAREER Award and an Alfred P. Sloan Fellowship. Sloan Foundation Fellowship, an Andrew Carnegie Fellowship, and the Heinz Family Foundation’s Twenty-Fifth Anniversary Recognition Award were bestowed upon him in recognition of his groundbreaking work redefining our comprehension of how globalization and technological advancements shape job prospects and incomes for American workers?
The assistant professor, housed within the Division of Digital Engineering and Computer Science at EECS, as well as principal investigator at the Computer Science and Artificial Intelligence Laboratory (CSAIL), has been appointed early career fellow. Beery’s work centers on developing laptop vision strategies capable of constructing comprehensive frameworks for large-scale environmental and biodiversity monitoring across diverse data modalities, addressing complex real-world challenges such as robustly capturing spatiotemporal correlations, coping with imperfect knowledge quality, and effectively classifying fine-grained categories amidst long-tailed distributions. Through partnerships with non-governmental organizations and authorities entities, she implements her global strategies, striving to enhance the diversity and accessibility of educational research in artificial intelligence via interdisciplinary skill development and training initiatives. Berry earned a Bachelor of Science in Electrical Engineering and Mathematics from Seattle College and a Doctorate in Computing and Mathematical Sciences from California Institute of Technology (Caltech), where she received the prestigious Amori Prize for her outstanding dissertation.
As a rising star in the field of electrical engineering and computer science, Dr., an assistant professor at LIDS and principal investigator, has earned the prestigious distinction of early career fellow. Farina’s research explores the confluence of artificial intelligence, computer science, operations research, and economics, lying at their nexus. He specializes in developing and refining methodologies for tackling complex decision-making processes in sequence, as well as solving intricate saddle-level problems that involve both convex and concave structures, often utilizing these strategies to uncover equilibriums in various video game contexts. Farina has also conducted in-depth research on the computational recreation principle and recently co-authored an article exploring the synergy between language models and strategic reasoning. A recipient of the prestigious NeurIPS Finest Paper Award, he has also held the esteemed position of Fb Fellow in both economics and computer science. His dissertation earned him the prestigious 2023 ACM SIGecom Doctoral Dissertation Award and was also recognized as one of only two recipients of the 2023 ACM Dissertation Award Honorable Mentions, a testament to its exceptional quality.
A renowned researcher and educator, Dr. Ghassemi (PhD ’17), has been named an early career fellow. As an affiliate professor in EECS and the Institute for Medical Engineering and Science, principal investigator at CSAIL and LIDS, and affiliate of the Abdul Latif Jameel Clinic for Machine Studying in Well being and the Institute for Knowledge, Methods, and Society, Ghassemi’s work has garnered significant attention. His research within the Wholesome ML Group focuses on creating a rigorous quantitative framework to design, develop, and deploy machine learning models that are robust and unbiased in health settings. Her work spans innovative initiatives that combine socially responsible practices with cutting-edge learning approaches to develop more inclusive and resilient models, yielding valuable insights with far-reaching impacts on policy, healthcare, and social equity.
Ghassemi has been recognized as one of Forbes’ 35 Innovators Under 35, and was awarded the 2018 Seth J. Awards and honors received include the prestigious Teller Award, the esteemed 2023 MIT Prize for Open Knowledge, the highly coveted 2024 NSF CAREER Award, and the distinguished Google Analytics Scholar Award. With a background in medicine, she founded the nonprofit Association for Health, Learning, and Innovation (AHLI), whose work has been prominently featured in leading publications such as The New York Times, Forbes, and CNN.
A principal investigator at CSAIL and assistant professor of electrical engineering and computer science has been designated an early career fellow. Kim’s research bridges the gap between natural language processing and machine learning, exploring the intersections between eco-friendly training and deployment of massive models, leveraging small-data learning, neuro-symbolic paradigms, grounded language acquisition, and the symbiosis between computational and human language comprehension. Affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL), Kim was awarded a PhD in computer science from Harvard University, an MS in knowledge science from New York University, an MA in statistics from Columbia University, and a BA in both mathematics and economics from Cornell University.
Further, the College of Toronto’s pc science affiliate professor Roger Grosse, PhD ’14, and Quebec AI Institute assistant professor David Rolnick, ’12, PhD ’18, have been appointed as senior and early career fellows, respectively.
