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美国卡内基梅隆大学池跃洁教授2021年9月8日在线上举办的浙江大学“智能信号处理” 国际工作坊上做了题为“用于低秩结构估计的可扩展鲁棒非凸优化方法”的讲座。
Yuejie Chi (池跃洁) received the B.E. degree (Hons.) in electrical engineering from Tsinghua University, Beijing, China, in 2007, and the M.A. and Ph.D. degrees in electrical engineering from Princeton University, in 2009 and 2012, respectively. She was with The Ohio State University from 2012 to 2017. Since 2018, she has been an Associate Professor with the Department of Electrical and Computer Engineering, Carnegie Mellon University, where she held the Robert E. Doherty Early Career Development Professorship, from 2018 to 2020. Her research interests lie in the theoretical and algorithmic foundations of data science, signal processing, machine learning, and inverse problems, with applications in sensing systems, broadly defined. Among others, she was a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE), the inaugural IEEE Signal Processing Society Early Career Technical Achievement Award for contributions to high-dimensional structured signal processing, and named the 2021 Goldsmith Lecturer by the IEEE Information Theory Society. She currently serves as an Associate Editor for IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, and IEEE Transactions on Pattern Recognition and Machine Intelligence.
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