Zishun's Homepage

About Me

I am a computer science Ph.D. student at the University of Illinois at Chicago (UIC), advised by Prof. Xinhua Zhang, since 2021. Also, I am fortunate to collaborate with Prof. Ian Kash and Prof. Lev Reyzin. My research interest spans reinforcement learning and optimization.

Prior to that, I received my master's degree in Industrial Engineering & Operations Research from UIC, under the advisory of Prof. Mengqi Hu, and my bachelor's degree from Huazhong University of Science and Technology.

Publications/Manuscripts

• [1] \(\mathcal{B}\)-Coder: On Value-Based Deep Reinforcement Learning for Program Synthesis. [PDF]
  Zishun Yu, Yunzhe Tao, Liyu Chen, Tao Sun and Hongxia Yang
  FMDM@NeurIPS (Foundation Models for Decision Making Workshop), 2023
  

• [2] Actor-Critic Alignment for Offline-to-Online Reinforcement Learning. [PDF][Code]
  Zishun Yu and Xinhua Zhang
  ICML (International Conference on Machine Learning), 2023
  

• [3] †Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs. [PDF]
  Ian A. Kash, Lev Reyzin and Zishun Yu* - Preprint, 2023
  

• [4] Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats. [PDF][Code]
  Hongwei Jin, Zishun Yu and Xinhua Zhang
  NeurIPS (Neural Information Processing Systems), 2022
  

• [5] Orthogonal Gromov-Wasserstein Discrepancy with Efficient Lower Bound. [PDF][Code]
  Hongwei Jin, Zishun Yu and Xinhua Zhang
  UAI (Uncertainty in Artificial Intelligence), 2022
  

• [6] Deep Reinforcement Learning with Graph Representation for Vehicle Repositioning. [PDF]
  Zishun Yu and Mengqi Hu
  IEEE-ITS (IEEE Transactions on Intelligent Transportation Systems), 2021
  

Professional Experience

• Research Scientist Intern
  TikTok/ByteDance, Chicago IL
  Aug 2023 - Sept 2023

• Research Scientist Intern
  TikTok/ByteDance, Bellevue WA
  May 2023 - Aug 2023

Awards

• NSF TRIPODS Graduate Fellowship (Summer 2021) [Link]
  Advisor: Prof. Ian Kash and Prof. Lev Reyzin.

• MITACS Globalink Undergraduate Research Internship (Summer 2016)
  York University, Canada

Professional Services

Conference Reviewer:

• Conference on Neural Information Processing Systems (NeurIPS) , 2022, 2023

• International Conference on Machine Learning (ICML) , 2023

• International Conference on Learning Representations (ICLR) , 2023, 2024

• International Conference on Artificial Intelligence and Statistics (AISTATS) , 2023, 2024

• Conference on Uncertainty in Artificial Intelligence (UAI) , 2023

Journal Reviewer:

• Transactions on Machine Learning Research (TMLR) , 2023 -

• IEEE Computational Intelligence Magazine (CIM) , 2023 -

Competitions

Kaggle competition Master¹.

• [Kaggle] Santa's Annual Optimization Challenge 2022 [Link]
  Gold medal          (rank 8/875)
  Robotics, Planning, Optimization, Combinatorics, TSP

• [Kaggle] Santa's Annual Optimization Challenge 2021 [Link]
  Silver medal        (top 4%)
  Optimization, Combinatorics, Superpermutation, Coloured TSP

• [Kaggle] Santa's Annual Optimization Challenge 2019 [Link]
  Silver medal        (top 5%)
  Optimization, Combinatorics, Assignment Problem, Mixed Integer Programing

• [Kaggle] Catheter and Line Position Challenge [Link]
  Bronze medal     (top 8%)
  Classification, Computer Vision, Medical Image

(¹Kaggle official ranking system.)