Biography
Tianyi Chen is an associate professor with Cornell Electrical and Computer Engineering at Cornell Tech. Prior to joining Cornell, he was an associate professor of the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI), where his research was jointly supported by the RPI-IBM Artificial Intelligence Research Partnership. Chen received his Ph.D. degree from the University of Minnesota in 2019 and earned his B.Sc. degree with highest honors from Fudan University in 2014.
Chen is the inaugural recipient of the IEEE Signal Processing Society Best Ph.D. Dissertation Award (2020), a recipient of the NSF CAREER Award (2021), and a recipient of the Amazon Research Award (2022). He is also a co-author of papers recognized with the Best Student Paper Award at the NeurIPS Federated Learning Workshop (2020), IEEE ICASSP (2021), and the IEEE Signal Processing Society Young Author Best Paper Award (2024).
Research Interests
Chen’s research focuses on the theoretical and algorithmic foundations of optimization and machine learning, with applications spanning AI —such as generative model fine-tuning and alignment, few-shot learning, and federated learning—as well as emerging computing systems, including next-generation wireless networks and analog in-memory computing.
- Statistics and Machine Learning
- Signal and Image Processing
- Mathematical Optimization
- Information, Networks, and Decision Systems
Teaching Interests
- ECE 5290/7290 – Distributed Optimization for ML and AI
- ECE 5110 – Random Signals in Signal Processing and Communications
Select Publications
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Zhaoxian Wu, Quan Xiao, Tayfun Gokmen, Omobayode Fagbohungbe, and Tianyi Chen, “Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions,” Proc. of Neural Information Processing Systems (NeurIPS), San Diego, CA, December 2-7, 2025.
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Han Shen, Quan Xiao, and Tianyi Chen, “On Penalty-based Bilevel Gradient Descent Method” Mathematical Programming, February 2025.
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Lisha Chen, Heshan Fernando, Yiming Ying, and Tianyi Chen, “Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance,” Journal of Machine Learning Research, vol 25, pp. 1-53, 2024.
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Tianyi Chen, Yuejiao Sun, and Wotao Yin, “Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems,” Proc. of Neural Information Processing Systems (NeurIPS), Virtual, December 6-14, 2021.
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Tianyi Chen, Georgios Giannakis, Tao Sun and Wotao Yin, “LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning,” Proc. of Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 3-8, 2018.
Select Awards and Honors
- Young Author Best Paper Award, IEEE Signal Processing Society (SPS) 2024
- Amazon Research Awards, AWS AI 2022
- CAREER Award, National Science Foundation 2021
- ICASSP Best Student Paper Award, Senior Author 2021
- Best Ph.D. Dissertation Award, IEEE Signal Processing Society (SPS) 2020
Education
- Ph.D., electrical and computer engineering, University of Minnesota 2019
- M.S., electrical and computer engineering, University of Minnesota 2016
- B.S., communication science and engineering, Fudan University 2014
