I am a Ph.D. student majoring in Computer Science at Shanghai Jiao Tong University. I obtained my B.Eng. majoring in CS at SJTU as a member of ACM Honors Class, which is an elite CS program at SJTU for the top 5% talented students.


Undergraduate Researcher

2018.7 - 2019.7
Data Driven Software Technology Laboratory, Shanghai Jiao Tong University
  • I am an undergraduate researcher, advised by Prof. Yanmin Zhu.
  • Focus on urban computing and urban data mining.
  • Conduct a comprehensive study on exploring.

Research Intern

2019.8 - 2020.1
Pennsylvania State University
  • I am an research intern, advised by Prof. Jessie Li.
  • Focus on “learning to simulate”, making the simulator closer to the real world.
  • Try to use the combination of physic model and deep neural networks, for a good performance when the data is insufficient.

Undergraduate Researcher

2020.2 - 2020.6
APEX Data & Knowledge Management Laboratory, Shanghai Jiao Tong University
  • I am an undergraduate researcher, advised by Prof. Weinan Zhang.
  • Focus on improve the genaralization ability of traffic signal control models.
  • Propose a novel meta-RL framework and conduct extensive experiments.

Ph.D. Researcher

2020.9 - present
Artificial Intelligence Institute, Shanghai Jiao Tong University
  • I am an Ph.D. researcher, advised by Prof. Hongyuan Zha and Prof. Junchi Yan.
  • Focus on utilizing machine learning methods to solve combinatorial optimization problems.


  • Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
  • Chang Liu, Zetian Jiang, Runzhong Wang, Lingxiao Huang, Pinyan Lu, Junchi Yan.
    ICLR, 2023
  • A Survey for Solving Mixed Integer Programming via Machine Learning
  • Jiayi Zhang, Chang Liu, Xijun Li, Hui-Ling Zhen, Mingxuan Yuan, Yawen Li, Junchi Yan.
  • Self-supervised Learning of Visual Graph Matching
  • Chang Liu*(equal contribution), Shaofeng Zhang*, Xiaokang Yang, Junchi Yan.
    ECCV, 2022
  • Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning
  • Chang Liu, Chenfei Lou, Runzhong Wang, Yuhan Xi, Li Shen, Junchi Yan.
    ICML, 2022
  • Knowledge-based Residual Learning
  • Guanjie Zheng, Chang Liu, Hua Wei, Porter Jenkins, Chacha Chen, Tao Wen, Zhenhui Li.
    IJCAI, 2021
  • Rebuilding City-Wide Traffic from Multi-Source Data
  • Guanjie Zheng*, Chang Liu*(equal contribution), Hua Wei, Chacha Chen, Zhenhui Li.
    ICDE, 2021
  • GeneraLight Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning
  • Chang Liu*(equal contribution), Huichu Zhang*, Weinan Zhang, Guanjie Zheng, Yong Yu
    CIKM, 2020
  • Learning to Simulate on Sparse Trajectory Data (Best ADS Paper Award)
  • Hua Wei, Chacha Chen, Chang Liu, Guanjie Zheng, Zhenhui Li
    ECML-PKDD, 2020
  • CityFlow A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
  • Huichu Zhang, Siyuan Feng, Chang Liu, Yaoyao Ding, Yichen Zhu, Zihan Zhou, Weinan Zhang, Yong Yu, Haiming Jin, Zhenhui Li
    WWW, 2019


    Reinforcement Learning for Combinatorial Optimization Problems - We maintain a list of resources that utilize machine learning technologies to solve combinatorial optimization problems (ML4CO), which has gained more than 700 stars on Github.
    Generalized Traffic Signal Control System - We propose a novel meta-RL framework GeneraLight for traffic light signal control models, which can significantly improve their generalization ability to different environments.
    Learning to Simulate - We focus on reducing the gap between simulator and the real world, finding solutions to different problems.
    City Traffic Simulator - We Built a city traffic simulator, serving reinforcement learning algorithm as a multi-agent reinforcement learning environment.
    Shared Bike System in Urban Computing - Focusing on transfer learning and spatial-temporal analysis in shared bike system, I wrote a paper proposing a model combined with principle component analysis, discrete wavelet transform and attention mechanism.
    Mx Compiler - I designed a compiler implemented in Java from scratch, translating a Java-and-C-like language to NASM, and implemented optimizations for the compiler, faster than gcc O1 on some test sets.
    Shor Algorithm - A simple implement of shor algorithm in quantum computing, written by a new quantum language called Q#.