Miscellaneous
Tips for Presentations
How to do academic presentation: Tips and Tricks, from UIUC.
How to speak, MIT How to Speak, IAP 2018 Instructor: Patrick Winston.
Old News
Sep. 2023, our paper "Distributionally Robust Model-based Reinforcement Learning with Large State Spaces" is online!
Jul. 2023, I organized a session "Theory and Applications in the Interface of ML and OR" at International Conference on Stochastic Programming in Davis.
May. 2023, we organized a mini-symposium "Robust Learning in Static and Dynamic Environment" at SIAM Conference on Optimization in Seattle. Featuring 12 amazing talks!
Jan. 2023, our updated paper "Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization" is online! It contains generalization bounds from both algorithm-agnostic uniform convergence and algorithm-specific stability analysis.
Dec. 2022, I gave a presentation at EPFL CIS NeurIPS Event and demonstrated the poster at NeurIPS OPT2022 Workshop of paper "Uniform Convergence and Generalization for Nonconvex Stochastic Minimax Problems".
Oct. 2022, I presented "Solving Stochastic Nonconvex Optimization to Global Optimality with Implicit Convex Reformulation and Its Applications in Network Revenue Management" in INFORMS Annual Meeting 2022.
Sep. 2022, I start a new position as a postdoc researcher at the Risk Analytics and Optimization Lab at EPFL.
May. 2022, I successfully defended my PhD thesis!
May. 2022, our paper "Uniform Convergence and Generalization for Nonconvex Stochastic Minimax Problems" is online!
May. 2022, our paper "Efficient Algorithms for Minimizing Compositions of Convex Functions and Random Functions and Its Applications in Network Revenue Management" is selected as oral presentation at SIG MSOM 2022 and is selected as spotlight presentation at RMP 2022.
Mar. 2022, I received the William A Chittenden II Award from ISE department at UIUC. Thanks!
Mar. 2022, Liang Zhang joined ODI as a PhD student. Welcome!
Nov. 2021, I pass the Preliminary exam of my dissertation proposal.
Sep. 2021, our paper "On the Bias-Variance-Cost Tradeoff of Stochastic Optimization" got accepted to NeurIPS 2021.
Sep. 2021, Liang deposited his master thesis.
Jun. 2021, I started visiting the Institute of Machine Learning of ETH Zurich at Switzerland. It's nice to be back.
May. 2021, I submitted two papers to NeurIPS 2021.
Mar. 2021, I started to co-supervise the master thesis of Liang Zhang at ETH Zurich.
Feb. 2021, I co-chaired the Optimization, Control, and Reinforcement Learning Session at the 16th CSL Student Conference.
Sep. 2020, I received the Yee's Memorial Fellowship from the Grainger College of Engineering at UIUC.
Sep. 2020, our paper "Biased Stochastic First-order Methods for Conditional Stochastic Optimization and Its Applications in Meta Learning" got accepted by NeurIPS 2020.
May. 2020, my first paper "Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization" got accepted by SIAM Journal on Optimization.
Feb. 2020, I presented "Biased Stochastic Gradient Descent for Conditional Stochastic Optimization" at the 15th CSL Student Conference. It won the Best Presentation Award in recognition of high-quality research, professional slides, and elegant eloquence.