Wenhao Ding



Wenhao Ding

丁文浩


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

Contact: wenhaod AT andrew DOT cmu DOT edu

Github / Google Scholar / LinkedIn / Resume

I am a second-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 interested in deep generative models, structural data representation, and causal discovery. Specifically, I focus on understanding, modeling and generating safety-critical scenarios for training and evaluating intelligent robots.

News & Updates

[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.

[2020/01] One paper accepted to IEEE International Conference on Robotics and Automation (ICRA) 2020.

Selected Publications ('*' indicates equal contribution)

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]

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

Wenhao Ding, Baimimng Chen, Bo Li, Kim Ji Eun, Ding Zhao
IEEE Robotics and Automation Letters (with 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 and 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 and 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 and 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 and 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 and Huihuan Qian
IEEE International Conference on Robotics and Biomimetics (ROBIO) 2018, Malaysia.

[arXiv] [code] [video] [bibtex]

Academic Services

Conference Reviewer: NeurIPS 2021, ICRA 2019/2020/2021, IROS 2020/2021, ICME 2020/2021

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

    Updated on April 20th, 2021

                 
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