Zifan Xu

LARG | UTCS | Texas Robotic | zfxu [at] utexas.edu

I am a Ph.D. student of Computer Science at University of Texas at Austin. I am very honored to be advised by Prof. Peter Stone. I have general interests in reinforcement learning, meta learning, curriculum learning, and their applicaitons in robotics. My primiary focus is to apply deep reinforcement learning for mobile robot autonomous navigation.

Before I started the CS program, I recieved master’s and bachelor’s degrees in Physics, but was lucky to find my passion in artificial intellegence. Feel free to reach out to me if you are curious about my experience and research!

Contact: Email / Github / Google Scholar / Twitter / CV

News

Jul 22, 2022 I presented two papers for DARL workshop at ICML 2022.
May 26, 2022 We organized The BARN Challenge at ICRA 2022 in Philadelphia.

Publications

Preprint

  1. Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis
    Zifan Xu, Anirudh Nair, Xuesu Xiao, and Peter Stone
  2. DynaBARN: Benchmarking Metric Ground Navigation in Dynamic Environments
    Anirudh Nair, Fulin Jiang, Kang Hou, Zifan Xu, Shuozhe Li, Xuesu Xiao, and Peter Stone
    Submitted to International Symposium on Safety, Security, and Rescue Robotics (SSRR) 2023
  3. Model-Based Meta Automatic Curriculum Learning
    Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Yuqian Jiang, Reuth Mirsky, Bo Liu, and Peter Stone
    Submitted to Association for the Advancement of Artificial Intelligence (AAAI) 2023

Journal

  1. APPL: Adaptive Planner Parameter Learning
    Xuesu Xiao, Zizhao Wang, Zifan Xu, Bo Liu, Gauraang Dhamankar, Anirudh Nair, Garrett Warnell, and Peter Stone
    Robotics and Autonomous Systems

Conference

  1. Causal Dynamics Learning for Task-Independent State Abstraction
    Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, and Peter Stone
    In Proceedings of the 39th International Conference on Machine Learning (ICML2022),
  2. APPLR: Adaptive Planner Parameter Learning from Reinforcement
    Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, and Peter Stone
    In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021),
  3. Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning
    Zifan Xu, Xuesu Xiao, Garrett Warnell, Anirudh Nair, and Peter Stone
    In Proceedings of the 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021),
  4. A Scavenger Hunt for Service Robots
    Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter Stone
    In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021),

Workshop / Extended Abstract / Technical Report

  1. Task Factorization in Curriculum Learning
    Reuth Mirsky, Shahaf S. Shperberg, Yulin Zhang, Zifan Xu, Yuqian Jiang, Jiaxun Cui, and Peter Stone
    In Decision Awareness in Reinforcement Learning (DARL) workshop at the 39th International Conference on Machine Learning (ICML),
  2. GOLD-FACTUAL: Learning to Generate Faithful Summaries from Models’ Generations
    Zifan Xu, and Liyan Tang
    CS394R Final Project
  3. Model-Based Meta Automatic Curriculum Learning
    Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yulin Zhan, Yuqian Jiang, Bo Liu, and Peter Stone
    In Decision Awareness in Reinforcement Learning (DARL) workshop at the 39th International Conference on Machine Learning (ICML),