¡Hola!
I am a second-year Ph.D. student at Department of Electrical and Computer Engineering, Princeton University, advised by Prof. Jason M. Klusowski. Previously, I obtained B.Sc. in Computer Science with First Class Honours from the Chinese University of Hong Kong, with a minor in Mathematics.
My research interest lies broadly in optimization, statistics, and their association with the theoretical foundations of modern machine learning. Recently, I am in particular focused on the decision theory behind language model decoding strategies. I have also worked on first-order methods for non-convex optimization problems such as federated learning and signal processing.
My hobbies include piano, soccer (football), photography, among others.
Publications
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Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies.
Sijin Chen, Omar Hagrass, and Jason M. Klusowski, Preprint, 2024. -
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression.
Sijin Chen, Zhize Li, and Yuejie Chi, International Conference on Artificial Intelligence and Statistics (AISTATS), 2024. -
Non-Convex Joint Community Detection and Group Synchronization via Generalized Power Method.
Sijin Chen, Xiwei Cheng, and Anthony Man-Cho So, International Conference on Artificial Intelligence and Statistics (AISTATS), 2024. -
CIA-SSD: Confident IoU-Aware Single-Stage Object Detector from Point Cloud.
Wu Zheng, Weiliang Tang, Sijin Chen, Li Jiang, and Chi-Wing Fu, AAAI Conference on Artificial Intelligence (AAAI), 2021.
Teaching
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SML310: Research Projects in Data Science
Assistant in Instruction, 2024 Fall
Awards
- Gordon Y. S. Wu Fellowship in Engineering
- Hong Kong Government Scholarship for Outstanding Performance
- VTech Group of Companies Scholarship
Professional Service
- Reviewer: International Conference on Learning Representations (ICLR)
Curriculum Vitae
View the PDF version here.