Regular biography
Yuejie Chi is a Professor in the Department of Statistics and Data Science at Yale University. His research interests include statistical signal processing, machine learning, and data science. He is affiliated with the Department of Statistics and Data Science and can be contacted via email at yuejie.chi@yale.edu. His professional website provides additional information about his work and academic profile.
Scholar-generated biography
Yuejie Chi is a Dilley Professor at Yale University, specializing in data science, generative AI, signal processing, and reinforcement learning. His research focuses on developing advanced algorithms for signal recovery, matrix completion, and nonconvex optimization, with applications in compressed sensing, phase retrieval, and machine learning. Chi's work explores the interplay between statistical guarantees and computational efficiency, particularly in handling noisy and incomplete data. He has contributed to the development of methods such as atomic norm minimization, structured matrix completion, and natural policy gradient approaches. His research bridges theoretical insights with practical implementations, enhancing the robustness and scalability of data-driven systems.