Yi Chen
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Assistant Professor Contact:Email: yichen@ust.hk |
About me
I am an assistant professor at departement of Industry Engineering and Decision Analytics, Hong Kong University of Science and Technology (HKUST) since 2022. Before that, I obtained my PhD degree from department of Industrial Engineering and Management Science, Northwestern University and bachelor degree from department of statistics, University of Science and Technology of China (USTC). My research field is at the interface of opeartions research/management and machine learning. My current research interest is designing data-driven algorithms to solve real problems in operations research/management. I am also interested in empirical research related to service system operations.
Research
Stochastic Simulation
ε-Strong Simulation for Fractional Brownian Motion and Related Stochastic Differential Equations: Yi Chen, Jing Dong and Hao Ni, Mathematics of Operations Research, 2021
Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion: Yi Chen, Jing Dong, Jinglin Chen, Jian Peng and Zhaoran Wang, 2019 International Conference on Learning Representations (ICLR)
On the Almost Sure Convergence Rate for a Series Expansion of Fractional Brownian Motion: Yi Chen and Jing Dong, Proceedings of the 2019 Winter Simulation Conference (WSC)
Can We Do Better than Random Start? The Power of Data Outsourcing: Yi Chen, Jing Dong, Xin Tong and Bo Shen, under review at INFROMS Journal on Computing
Data-Driven Decision Making and Statistical Learning
A Primal-Dual Approach to Constrained Markov Decision Processes with Applications to Queuing Scheduling and Inventory Management: Yi Chen, Jing Dong, Zhaoran Wang and Chuheng Zhang, minor revision at Management Science
Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection: Yi Chen, Yining Wang, Xinyuan Ethan Fang, Zhaoran Wang and Runze Li, Journal of the American Statistical Association, 2022
Constrained Ensemble Exploration for Unsupervised Skill Discovery: Chenjia Bai, Rushuai Yang, Qiaosheng Zhang, Kang Xu, Yi Chen, Ting Xiao, Xuelong Li, 2024 International Conference on Machine Learning (ICML)
Variance-Dependent Regret Bounds for Non-stationary Linear Bandits: Zhiyong Wang, Jize Xie, Yi Chen, John Lui, Dongruo Zhou, 2024 International Conference on Machine Learning 2024 Workshop: FoRLaC
Beyond the Limit of Weight-Sharing: Pioneering Space-Evolving NAS with Large Language Models: Xiu Su, Shan You, Hongyan Xu, Xiuxing Li, Jun Long, Yi Chen, Chang Xu, 2024 International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Contrastive Learning from Pairwise Measurements: Yi Chen, Zhuoran Yang, Yuchen Xie, and Zhaoran Wang, 2018 Advances in Neural Information Processing Systems (NeurIPS)
Empirical Operations Management
The Impact of Historical Workload on Nurses’ Perceived Workload: Carri W. Chan, Yi Chen, Jing Dong, and Sarah C. Rossetti, major revision at Management Science
Beyond Order-Based Workload: A Retrospective Cohort Study in Intensive Care Units: Yi Chen, Carri W. Chan , Jing Dong, Natalie Yip, Emily Jackson, and Sarah C. Rossetti, Journal of Nursing Management, 2024
Discount Signaling When Customers Search: A Structural Estimation of Click-then-Purchase Behavior on Online Retail Platform: Yi Chen, Jing Dong and Fanyin Zheng, to be submitted
Awards
Terminal Year Fellowship (2020), Graduate School, Northwestern University
Arthur P. Hurter Award (2017), Department of IEMS, Northwestern University
The 35th Guo Moruo Award (2016) University of Science and Technology of China, (highest honor for undergraduate student)
Exceptional Graduate Award (2016), University of Science and Technology of China
National Scholarship (2015), Ministry of Education of P.R. China
Industry Experience
Alibaba, Seattle, WA (Jun-Sep, 2019): Research Scientist Intern, working on demand estimation.
Teaching Experience
Lecture courses: IEDA 2520 Probability for Engineers, IEDA 3300 Industrial Database System
Teaching Assistant courses: IEMS 303 Statistics, IEMS 315 Stochastic Models, IEMS 313 Foundations of Optimization, IEMS 343 Project Management, IEMS 345 Negotiations for Engineers and IEMS 461 Stochastic Processes I (Ph.D. core).