Yuejie Chi
Sense of Wonder Group Endowed Professor in AI Systems
Department of Electrical and Computer Engineering
Machine Learning Department and CyLab (by courtesy)
Carnegie Mellon University
Short Bio  /  CV  /  Google Scholar


I am the Sense of Wonder Group Endowed Professor of Electrical and Computer Engineering in AI Systems at Carnegie Mellon University. I am also an affiliated faculty member with the Machine Learning Department and CyLab. My department homepage is here.

My research interests lie in the theoretical and algorithmic foundations of data science, machine learning, signal processing and inverse problems, with applications in sensing, imaging, decision making, and societal systems, broadly defined. The problems my group studies are often interdisciplinary in nature, lying at the intersection of statistics, learning, optimization, and sensing. My current focus is on reinforcement learning, nonconvex statistical estimation, distributed and federated learning, and generative AI. Specific lines of research topics can be found here.

I have been lucky to receive a couple of awards for my work, including Presidential Early Career Award for Scientists and Engineers (PECASE) from the White House, the highest honor bestowed by the United States Government to outstanding early-career scientists and engineers who show exceptional promise for leadership in science and technology. In 2019, I received the inaugural IEEE Signal Processing Society Early Career Technical Achievement Award for contributions to high-dimensional structured signal processing. In addition, I received 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. At CMU, I received the College of Engineering Philip and Marsha Dowd Fellowship in 2023, and held the inaugural Robert E. Doherty Career Development Professorship during 2018-2020.

I am an IEEE Fellow (Class of 2023) for contributions to statistical signal processing with low-dimensional structures. [ECE News] [SCS News]

I also had the privilege to deliver plenary, keynote and tutorial talks at several conferences and workshops, with more materials shared here. I was named the Goldsmith Lecturer by IEEE Information Theory Society in 2021, a Distinguished Lecturer by IEEE Signal Processing Society for 2022-2023, and a Distinguished Speaker by ACM for 2023-2026.

Previously I was with the Dept. of Electrical and Computer Engineering and the Dept. of Biomedical Informatics at The Ohio State University until 2017. I completed my Ph.D. in Electrical Engineering from Princeton University in 2012, where I was fortunate to be advised by Prof. Robert Calderbank. I received a M.A. in Electrical Engineering from Princeton University in 2009, and a B.Eng. in Electronic Engineering from Tsinghua University in 2007.

I have an Erdos number of 3.

Notes to prospective students outside CMU: There is on expectation 1 slot in my group every year, however this expectation will be zero for Fall 2024. Unfortunately, I am not able to respond to most (nearly all!) inquiries about suitability in my group due to the volume of emails I receive. Instead, please apply directly to the ECE department and list me as a faculty of interest. Occasionally, I take summer interns and visitors with strong mathematical backgrounds.

Notes to students at CMU: Please contact me directly if you're interested in research projects in my group. Interested students should have a strong background in mathematics and programming.

Upcoming

Selected Recent Papers

Contact

  • Office: Porter Hall B25

  • Mailing address: 5000 Forbes Ave., Pittsburgh, PA 15213

  • Email: first+last at cmu dot edu = first+c at andrew dot cmu dot edu