Wenhao Ding


Wenhao Ding

丁文浩


Ph.D. Candidate, Department of Mechanical Engineering, Carnegie Mellon University.

M.S., Machine Leaning Department, Carnegie Mellon University.

Github / Google Scholar / LinkedIn / CV / Email

I am a third-year Ph.D. student advised by Prof. Ding Zhao of Safe AI Lab. I am also co-advised by Prof. Bo Li of Secure Learning Lab. I received my Bachelor degree from Electronic Engineering, Tsinghua University.

I am an FPV drone flyer. Check my gallery.

Research Highlights

My research goal is to build robust and effective robots that can truly understand the causal mechanisms of the physical world. Specifically, I am interested in the following topics:

  • Controllable Generative Models. Generating safety-critical scenarios for robust robots develepment.
  • Interpretable Adversarial Examples. Creating semantically understandable examples to evaluate robutness.
  • Causal Discovery. Discover the underlying causality from observational and interventional time series data.

    • News & Updates

    2021/05 - I will start my summer intern in Bosch Center for Artificial Intelligence.

    2021/02 - One paper accepted to IEEE Robotics and Automation Letter (with ICRA 2021).

    2020/09 - One paper accepted to Neural Information Processing Systems (NeurIPS) 2020.

    2020/06 - One paper accepted to International Conference on Intelligent Robots and Systems (IROS) 2020.

    Selected Publications

    CausalAF: Causal Autoregressive Flow for Goal-Directed Safety-Critical Scenes Generation

    Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao
    Preprint arXiv:2110.13939

    arXiv / code / bibtex

    Semantically Controllable Scene Generation with Guidance of Explicit Knowledge

    Wenhao Ding, Bo Li, Kim Ji Eun, Ding Zhao
    Preprint arXiv:2106.04066

    arXiv / code / bibtex

    Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems

    Mansur Arief, Yuanlu Bai, Wenhao Ding, Shengyi He, Zhiyuan Huang, Henry Lam, Ding Zhao
    Preprint arXiv:2111.02204

    arXiv / code / bibtex

    Deep Probabilistic Accelerated Evaluation: A Certifiable Rare-Event Simulation Methodology for Black-Box Autonomy

    Mansur Arief*, Zhiyuan Huang*, Guru Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao
    Artificial Intelligence and Statistics (AISTATS) 2021

    arXiv / code / bibtex

    Context-Aware Safe Reinforcement Learning for Non-Stationary Environments

    Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Liang Li, Ding Zhao
    IEEE International Conference on Robotics and Automation (ICRA) 2021

    arXiv / code / bibtex

    Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation

    Wenhao Ding, Baiming Chen, Bo Li, Kim Ji Eun, Ding Zhao
    IEEE Robotics and Automation Letters (and ICRA 2021)

    arXiv / code / bibtex

    Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes

    Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao
    Neural Information Processing Systems (NeurIPS) 2020, Vancouver

    arXiv / code / bibtex

    Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method

    Wenhao Ding, Baiming Chen, Minjun Xu, Ding Zhao
    International Conference on Intelligent Robots and Systems (IROS) 2020, Las Vegas

    arXiv / code / video / bibtex

    CMTS: Conditional Multiple Trajectory Synthesizer for Generating Safety-critical Driving Scenarios

    Wenhao Ding, Mengdi Xu, Ding Zhao
    International Conference on Robotics and Automation (ICRA) 2020, Paris

    arXiv / code / supplementary / bibtex

    A New Multi-vehicle Trajectory Generator to Simulate Vehicle-to-Vehicle Encounters

    Wenhao Ding, Wenshuo Wang, Ding Zhao
    International Conference on Robotics and Automation (ICRA) 2019, Montreal

    arXiv / code / supplementary / bibtex

    Hierarchical Reinforcement Learning Framework towards Multi-agent Navigation

    Wenhao Ding, Shuaijun Li, Huihuan Qian
    IEEE International Conference on Robotics and Biomimetics (ROBIO) 2018, Malaysia

    arXiv / code / bibtex

    Vehicle Pose and Shape Estimation through Multiple Monocular Vision

    Wenhao Ding, Shuaijun Li, Guilin Zhang, Xiangyu Lei, Huihuan Qian
    IEEE International Conference on Robotics and Biomimetics (ROBIO) 2018, Malaysia

    arXiv / code / video / bibtex

    Academic Services

    Conference Reviewer: ICML 2022, CVPR 2022, ICLR 2022, NeurIPS 2021, ICCV 2021, ICRA 2020-2021, IROS 2020-2021, ICME 2020-2022

    Journal Reviewer: IEEE RA-L, IEEE Access, IEEE T-ITS, IEEE TII, IEEE MM

     

      Updated on December 8th, 2021

                   
          Wenhao Ding © 2018-2021