Yuejie Chi

Yuejie Chi is the Sense of Wonder Group Endowed Professor of Electrical and Computer Engineering in AI Systems at Carnegie Mellon University, with affiliations in the Machine Learning Department and CyLab. She holds a Ph.D. from Princeton University and a B.Eng. (Hon.) from Tsinghua University. Her research focuses on theoretical foundations of data science, machine learning, signal processing, and inverse problems, with applications in sensing, imaging, and AI systems.

Her work emphasizes interdisciplinary approaches at the intersection of statistics, optimization, and sensing. Notable achievements include contributions to high-dimensional structured signal processing, for which she received the inaugural IEEE Signal Processing Society Early Career Technical Achievement Award (2019) and the PECASE (2019). She is an IEEE Fellow (2023) and has been recognized as a Goldsmith Lecturer (2021) and Distinguished Lecturer (2022).

Research interests include generative AI, reinforcement learning, nonconvex optimization, federated learning, and resource-efficient algorithms. Her group collaborates on projects such as data-driven materials research and agile waveform design for communication networks. She has advised numerous PhD students, many of whom have pursued academic and industry roles in leading institutions.

Awards include the SIAM Activity Group on Imaging Science Best Paper Prize (2024), NSF/ONR/AFOSR young investigator awards, and leadership roles in top conferences like NeurIPS, ICML, and IEEE workshops.