Machine learning expert Chi Jin named Sloan Research Fellow

Written by
Office of Engineering Communications
Feb. 21, 2024

The Arthur P. Sloan Foundation has named Chi Jin a 2024 Sloan Research Fellow, recognizing his expertise and leadership in machine learning.

The fellowship honors creative early-career researchers in the sciences and social sciences. Five Princeton faculty members were awarded Sloan fellowships this year, and 248 Princeton faculty have received Sloan fellowships since they were first awarded in 1955. More than 1000 researchers are nominated each year for 126 fellowship slots.

Jin, an assistant professor of electrical and computer engineering, was awarded a fellowship in computer science. He studies the mathematical underpinnings of machine learning and artificial intelligence. His work focuses on theoretical foundations and algorithms in machine learning, optimization, statistics, and game theory, with a particular emphasis on reinforcement learning, a branch of machine learning that guides decision-making through rewards and penalties. His research tackles key challenges in exploration-exploitation trade-offs, generalization within vast state spaces, collaboration and competition among multiple agents, and dealing with partially observed environments. These issues are crucial in real-world applications like robotics, autonomous vehicles, medical diagnostics and gaming.

Sloan Fellows receive a two-year, $75,000 fellowship that can be used flexibly. Fellowship candidates must be nominated by fellow scientists, and winners are selected based on a candidate’s research accomplishments, creativity and potential to become a leader in their field. Former fellows have gone on to receive some of science’s top honors, including Nobel Prizes and Fields Medals.

Jin earned his Ph.D. in computer science at the University of California-Berkeley, where he was advised by Michael I. Jordan. His research has won two best paper awards from workshops of the International Conference on Learning Representations and International Conference on Machine Learning, both of which are the top machine learning conferences. In 2023, Jin received an NSF CAREER Award and the Lawrence Keyes, Jr./Emerson Electric Co. Faculty Advancement Award from Princeton’s School of Engineering and Applied Science. He joined the Princeton faculty in 2019.