Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling. - Mengdi Xu; Peide Huang; Fengpei Li; Jiacheng Zhu; Xuewei Qi; Kentaro Oguchi 001; Zhiyuan Huang; Henry Lam; Ding Zhao (CoRR, 2021)

Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training. - Peide Huang; Mengdi Xu; Fei Fang 001; Ding Zhao (IJCAI, 2022)

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling. - Mengdi Xu; Peide Huang; Fengpei Li; Jiacheng Zhu; Xuewei Qi; Kentaro Oguchi 001; Zhiyuan Huang; Henry Lam; Ding Zhao (IROS, 2022)

Coalitional Fairness of Autonomous Vehicles at a T-Intersection. - Diana Gómez; Haohong Lin; Peide Huang; Corey Harper; Ding Zhao (ITSC, 2022)

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. - Peide Huang; Mengdi Xu; Jiacheng Zhu; Laixi Shi; Fei Fang 001; Ding Zhao (NeurIPS, 2022)

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. - Mengdi Xu; Zuxin Liu; Peide Huang; Wenhao Ding; Zhepeng Cen; Bo Li 026; Ding Zhao (CoRR, 2022)

Continual Reinforcement Learning with Group Symmetries. - Shiqi Liu 005; Mengdi Xu; Peide Huang; Yongkang Liu 005; Kentaro Oguchi 001; Ding Zhao (CoRR, 2022)

Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables. - Mengdi Xu; Peide Huang; Yaru Niu; Visak Kumar; Jielin Qiu; Chao Fang; Kuan-Hui Lee; Xuewei Qi; Henry Lam; Bo Li 026; Ding Zhao (AISTATS, 2023)

What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery. - Peide Huang; Xilun Zhang; Ziang Cao; Shiqi Liu 005; Mengdi Xu; Wenhao Ding; Jonathan Francis; Bingqing Chen; Ding Zhao (CoRL, 2023)

Continual Vision-based Reinforcement Learning with Group Symmetries. - Shiqi Liu 005; Mengdi Xu; Peide Huang; Xilun Zhang; Yongkang Liu 005; Kentaro Oguchi 001; Ding Zhao (CoRL, 2023)

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation. - Jielin Qiu; Jiacheng Zhu; Mengdi Xu; Peide Huang; Michael A. Rosenberg; Douglas Weber; Emerson Liu; Ding Zhao (ICASSP, 2023)

Characterizing Crowd Preferences on Stadium Facilities through Dynamic Inverse Reinforcement Learning. - Yiwen Dong 001; Peide Huang; Hae Young Noh (BuildSys, 2023)

GameVibes: Vibration-based Crowd Monitoring for Sports Games through Audience-Game-Facility Association Modeling. - Yiwen Dong 001; Yuyan Wu; Jesse R. Codling; Jatin Aggarwal; Peide Huang; Wenhao Ding; Hugo Latapie; Pei Zhang 001; Hae Young Noh (BuildSys, 2023)

Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging. - Jielin Qiu; Peide Huang; Makiya Nakashima; Jaehyun Lee; Jiacheng Zhu; W. H. Wilson Tang; Pohao Chen 001; Christopher Nguyen; Byung-Hak Kim; Debbie Kwon; Douglas Weber; Ding Zhao; et al. (CoRR, 2023)

Creative Robot Tool Use with Large Language Models. - Mengdi Xu; Peide Huang; Wenhao Yu 003; Shiqi Liu 005; Xilun Zhang; Yaru Niu; Tingnan Zhang; Fei Xia 002; Jie Tan 001; Ding Zhao (CoRR, 2023)

Construction of Virtual Simulation Teaching Platform for Risk Experimental Projects in VR Environment. - Gaocai Fu; Yu Jiang; Jun Xiao; Peide Huang; Xu Luo; Minhui Ni; Xianjv Liu (ICSIM, 2024)

Gradient shaping for multi-constraint safe reinforcement learning. - Yihang Yao; Zuxin Liu; Zhepeng Cen; Peide Huang; Tingnan Zhang; Wenhao Yu 003; Ding Zhao (L4DC, 2024)

CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectories. - Peide Huang; Wenhao Ding; Jonathan Francis; Bingqing Chen; Ding Zhao (CoRR, 2024)

EMOTION: Expressive Motion Sequence Generation for Humanoid Robots with In-Context Learning. - Peide Huang; Yuhan Hu; Nataliya Nechyporenko; Daehwa Kim; Walter Talbott; Jian Zhang (CoRR, 2024)

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning. - Yiwen Dong 001; Sung Eun Kim; Kornel Schadl; Peide Huang; Wenhao Ding; Jessica Rose; Hae Young Noh (IEEE J. Biomed. Health Informatics, 2024)

ELEGNT: Expressive and Functional Movement Design for Non-anthropomorphic Robot. - Yuhan Hu; Peide Huang; Mouli Sivapurapu; Jian Zhang (CoRR, 2025)

Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications. - Xilun Zhang; Shiqi Liu 005; Peide Huang; William Jongwon Han; Yiqi Lyu; Mengdi Xu; Ding Zhao (IEEE Robotics Autom. Lett., 2025)

EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video. - Ryan Hoque; Peide Huang; David J. Yoon; Mouli Sivapurapu; Jian Zhang (CoRR, 2025)

EMOTION: Expressive Motion Sequence Generation for Humanoid Robots With In-Context Learning. - Peide Huang; Yuhan Hu; Nataliya Nechyporenko; Daehwa Kim; Walter Talbott; Jian Zhang 050 (IEEE Robotics Autom. Lett., 2025)