Scholar
Yuejie Chi
Google Scholar ID: h1NXfKYAAAAJ
Yale University
Citations & Impact
Citations
7,962
H-index
47
i10-index
97
Publications
20
Co-authors
151
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) from the White House, inaugural recipient of the IEEE Signal Processing Society Early Career Technical Achievement Award, SIAM Activity Group on Imaging Science Best Paper Prize, IEEE Signal Processing Society Young Author Best Paper Award, and young investigator awards from several agencies including NSF, ONR, and AFOSR. IEEE Fellow for contributions to statistical signal processing with low-dimensional structures. Delivered plenary, keynote, and tutorial talks at several conferences and workshops, including being named the Goldsmith Lecturer by IEEE Information Theory Society in 2021, Distinguished Lecturer by IEEE Signal Processing Society for 2022-2023, and Distinguished Speaker by ACM for 2023-2026.
Research Experience
- Currently, Professor of Statistics and Data Science at Yale University, with a secondary appointment in Computer Science. Previously, Professor of Electrical and Computer Engineering at Carnegie Mellon University, focusing on data science, generative AI, and reinforcement learning.
Education
- Since July 2025, Charles C. and Dorothea S. Dilley Professor of Statistics and Data Science at Yale University, with a secondary appointment in Computer Science. Previously, the Sense of Wonder Group Endowed Professor of Electrical and Computer Engineering in AI Systems at Carnegie Melon University, with affiliation in MLD and CyLab. Also spent some time as a visiting researcher at Meta's Fundamental AI Research (FAIR).
Background
- Research interests: Theoretical and algorithmic foundations of data science, generative AI, reinforcement learning, and signal processing, motivated by applications in scientific and engineering domains. Member of Yale Institute for Foundations of Data Science.
Miscellany
- Interested in recruiting strong candidates to work on the foundations and applications of generative AI and decision making.
