معرفی
Yuejie Chi is the Sense of Wonder Group Endowed Professor of Electrical and Computer Engineering in AI Systems at Carnegie Mellon University, holding courtesy appointments in the Machine Learning department and CyLab. She earned her Ph.D. and M.A. in Electrical Engineering from Princeton University and B.Eng. (Hon.) from Tsinghua University.
Her research centers on theoretical and algorithmic foundations of data science with expertise in signal processing, machine learning, and inverse problems. Key application areas include sensing, imaging, decision-making systems, and societal-scale data challenges. Her work bridges mathematical theory with real-world implementations through preconditioning techniques, overparameterization frameworks, and diffusion models for ill-conditioned estimation problems.
Major recognitions include:
- Presidential Early Career Award for Scientists and Engineers (PECASE)
- IEEE Signal Processing Society Early Career Technical Achievement Award
- IEEE Signal Processing Society Young Author Best Paper Award
- Goldsmith Lecturer by IEEE Information Theory Society
- Distinguished Lecturer by IEEE Signal Processing Society
- IEEE Fellow (2023) for contributions to statistical signal processing with low-dimensional structures
Dr. Chi serves as Associate Editor for IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, IEEE Transactions on Pattern Recognition and Machine Intelligence, Information and Inference: A Journal of the IMA, and SIAM Journal on Mathematics of Data Science. Her research program integrates theoretical guarantees with practical implementations in AI systems, particularly through collaborations with CyLab on security-aware data science frameworks.
