Nanostructured plasmonic devices and their applications. - Min Qiu; Qiang Li; Weichun Zhang; Lijun Meng; Ding Zhao; Xi Chen; Yiting Chen; Min Yan (ICAIT, 2013)

Plasmonic enhanced photothermal effects and its applications. - Min Qiu; Xi Chen; Yuechun Shi; Yiting Chen; Hanmo Gong; Ding Zhao; Xingxing Chen; Yuanqing Yang; Min Yan; Qiang Li (ICTON, 2014)

Nanowelding through plasmonic enhanced photothermal effects. - Min Qiu; Shuowei Dai; Guoping Liu; Hangbo Yang; Yuanqing Yang; Ding Zhao; Wei Wang; Qiang Li (ICTON, 2015)

Cloud Consumer Oriented Utility Model Research in Cloud Computing. - Xiaoxiong Liu; Ding Zhao; Yunchuan Qin; Zhuo Tang (UIC/ATC/ScalCom, 2015)

Enhancement of low-cost GNSS localization in connected vehicle networks using Rao-Blackwellized particle filters. - Macheng Shen; Ding Zhao; Jing Sun 003 (ITSC, 2016)

Accelerated Evaluation of Automated Vehicles using Piecewise Mixture Distribution Models. - Zhiyuan Huang; Ding Zhao; Henry Lam; David J. LeBlanc; Huei Peng (CoRR, 2016)

Accelerated Evaluation of Automated Vehicles based on Importance Sampling Techniques. - Ding Zhao; Henry Lam; Huei Peng; Shan Bao; David J. LeBlanc; Kazutoshi Nobukawa; Christopher S. Pan (CoRR, 2016)

Gap Acceptance During Lane Changes by Large-Truck Drivers - An Image-Based Analysis. - Kazutoshi Nobukawa; Shan Bao; David J. LeBlanc; Ding Zhao; Huei Peng; Christopher S. Pan (IEEE Trans. Intell. Transp. Syst., 2016)

Development and evaluation of two learning-based personalized driver models for car-following behaviors. - Wenshuo Wang 001; Ding Zhao; Junqiang Xi; David J. LeBlanc; J. Karl Hedrick (ACC, 2017)

Evaluation of automated vehicles in the frontal cut-in scenario - An enhanced approach using piecewise mixture models. - Zhiyuan Huang; Ding Zhao; Henry Lam; David J. LeBlanc; Huei Peng (ICRA, 2017)

Towards affordable on-track testing for autonomous vehicle - A Kriging-based statistical approach. - Zhiyuan Huang; Henry Lam; Ding Zhao (ITSC, 2017)

An accelerated testing approach for automated vehicles with background traffic described by joint distributions. - Zhiyuan Huang; Henry Lam; Ding Zhao (ITSC, 2017)

Optimization of vehicle connections in V2V-based cooperative localization. - Macheng Shen; Jing Sun 003; Ding Zhao (ITSC, 2017)

TrafficNet: An open naturalistic driving scenario library. - Ding Zhao; Yaohui Guo; Yunhan Jack Jia (ITSC, 2017)

Evaluation of automated vehicles encountering pedestrians at unsignalized crossings. - Baiming Chen; Ding Zhao; Huei Peng (Intelligent Vehicles Symposium, 2017)

Towards secure and safe appified automated vehicles. - Yunhan Jack Jia; Ding Zhao; Qi Alfred Chen; Zhuoqing Morley Mao (Intelligent Vehicles Symposium, 2017)

Analysis of unprotected intersection left-turn conflicts based on naturalistic driving data. - Xinpeng Wang 002; Ding Zhao; Huei Peng; David J. LeBlanc (Intelligent Vehicles Symposium, 2017)

Evaluation of a semi-autonomous lane departure correction system using naturalistic driving data. - Ding Zhao; Wenshuo Wang 001; David J. LeBlanc (Intelligent Vehicles Symposium, 2017)

The Impact of Road Configuration on V2V-Based Cooperative Localization. - Macheng Shen; Ding Zhao; Jing Sun 003 (VTC Spring, 2017)

Sequential experimentation to efficiently test automated vehicles. - Zhiyuan Huang; Henry Lam; Ding Zhao (WSC, 2017)

How Much Data is Enough? A Statistical Approach with Case Study on Longitudinal Driving Behavior. - Wenshuo Wang 001; Chang Liu 002; Ding Zhao (CoRR, 2017)

Evaluation of Lane Departure Correction Systems Using a Stochastic Driver Model. - Wenshuo Wang 001; Ding Zhao (CoRR, 2017)

From the Lab to the Street: Solving the Challenge of Accelerating Automated Vehicle Testing. - Ding Zhao; Huei Peng (CoRR, 2017)

Analysis of mandatory and discretionary lane change behaviors for heavy trucks. - Ding Zhao; Huei Peng; Kazutoshi Nobukawa; Shan Bao; David J. LeBlanc; Christopher S. Pan (CoRR, 2017)

Optimal design of three-planetary-gear power-split hybrid powertrains. - Weichao Zhuang; Xiaowu Zhang; Ding Zhao; Huei Peng; Lianmou Wang (CoRR, 2017)

A Kinodynamic Aggressive Trajectory Planner For Narrow Passages. - Yaohui Guo; Zhaolun Su; Dmitry Berenson; Ding Zhao (CoRR, 2017)

Semi-Interpenetrating Cooperative Localization in Connected Vehicle Networks. - Macheng Shen; Huajing Zhao; Jing Sun 003; Ding Zhao (CoRR, 2017)

A Versatile Approach to Evaluating and Testing Automated Vehicles based on Kernel Methods. - Zhiyuan Huang; Yaohui Guo; Henry Lam; Ding Zhao (CoRR, 2017)

Empirical Study of DSRC Performance Based on Safety Pilot Model Deployment Data. - Xianan Huang; Ding Zhao; Huei Peng (IEEE Trans. Intell. Transp. Syst., 2017)

Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques. - Ding Zhao; Henry Lam; Huei Peng; Shan Bao; David J. LeBlanc; Kazutoshi Nobukawa; Christopher S. Pan (IEEE Trans. Intell. Transp. Syst., 2017)

How Much Data Are Enough? A Statistical Approach With Case Study on Longitudinal Driving Behavior. - Wenshuo Wang 001; Chang Liu 002; Ding Zhao (IEEE Trans. Intell. Veh., 2017)

Evaluation of Lane Departure Correction Systems Using a Regenerative Stochastic Driver Model. - Wenshuo Wang 001; Ding Zhao (IEEE Trans. Intell. Veh., 2017)

A Versatile Approach to Evaluating and Testing Automated Vehicles based on Kernel Methods. - Zhiyuan Huang; Yaohui Guo; Mansur Arief; Henry Lam; Ding Zhao (ACC, 2018)

An Accelerated Approach to Safely and Efficiently Test Pre-Production Autonomous Vehicles on Public Streets. - Mansur Arief; Peter W. Glynn; Ding Zhao (ITSC, 2018)

Energy Efficiency and Emission Testing for Connected and Automated Vehicles Using Real-World Driving Data. - Yan Chang; Weiqing Yang; Ding Zhao (ITSC, 2018)

Evaluation of the Energy Efficiency in a Mixed Traffic with Automated Vehicles and Human Controlled Vehicles. - Xun Gong 007; Yaohui Guo; Yiheng Feng; Jing Sun 003; Ding Zhao (ITSC, 2018)

Synthesis of Different Autonomous Vehicles Test Approaches. - Zhiyuan Huang; Mansur Arief; Henry Lam; Ding Zhao (ITSC, 2018)

Accelerated Evaluation of Autonomous Vehicles in the Lane Change Scenario Based on Subset Simulation Technique. - Songan Zhang; Huei Peng; Ding Zhao; H. Eric Tseng (ITSC, 2018)

A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives. - Jiacheng Zhu; Wenshuo Wang 001; Ding Zhao (ITSC, 2018)

Cluster Naturalistic Driving Encounters Using Deep Unsupervised Learning. - Sisi Li; Wenshuo Wang 001; Zhaobin Mo; Ding Zhao (Intelligent Vehicles Symposium, 2018)

Deep Context: End-to-end Contextual Speech Recognition. - Golan Pundak; Tara N. Sainath; Rohit Prabhavalkar; Anjuli Kannan; Ding Zhao (SLT, 2018)

Designing Importance samplers to simulate Machine Learning Predictors via Optimization. - Zhiyuan Huang; Henry Lam; Ding Zhao (WSC, 2018)

Rare-Event simulation without Structural Information: a Learning-based Approach. - Zhiyuan Huang; Henry Lam; Ding Zhao (WSC, 2018)

Extracting V2V Encountering Scenarios from Naturalistic Driving Database. - Zhaobin Mo; Sisi Li; Diange Yang; Ding Zhao (CoRR, 2018)

Clustering of Naturalistic Driving Encounters Using Unsupervised Learning. - Sisi Li; Wenshuo Wang 001; Zhaobin Mo; Ding Zhao (CoRR, 2018)

Interpenetrating Cooperative Localization in Dynamic Connected Vehicle Networks. - Huajing Zhao; Zhaobin Mo; Macheng Shen; Jing Sun 003; Ding Zhao (CoRR, 2018)

An Accelerated Approach to Safely and Efficiently Test Pre-produced Autonomous Vehicles on Public Streets. - Mansur Arief; Peter W. Glynn; Ding Zhao (CoRR, 2018)

Fuel Economy and Emission Testing for Connected and Automated Vehicles Using Real-world Driving Datasets. - Yan Chang; Weiqing Yang; Ding Zhao (CoRR, 2018)

An Optimal LiDAR Configuration Approach for Self-Driving Cars. - Shenyu Mou; Yan Chang; Wenshuo Wang 001; Ding Zhao (CoRR, 2018)

Clustering of Driving Scenarios Using Connected Vehicle Datasets. - Wenshuo Wang 001; Aditya Ramesh; Ding Zhao (CoRR, 2018)

Understanding V2V Driving Scenarios through Traffic Primitives. - Wenshuo Wang 001; Weiyang Zhang; Ding Zhao (CoRR, 2018)

An "Xcity" Optimization Approach to Designing Proving Grounds for Connected and Autonomous Vehicles. - Rui Chen 030; Mansur Arief; Ding Zhao (CoRR, 2018)

Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters. - Wenhao Ding; Wenshuo Wang 001; Ding Zhao (CoRR, 2018)

Extracting Traffic Primitives Directly From Naturalistically Logged Data for Self-Driving Applications. - Wenshuo Wang 001; Ding Zhao (IEEE Robotics Autom. Lett., 2018)

Accelerated Evaluation of Automated Vehicles Using Piecewise Mixture Models. - Zhiyuan Huang; Henry Lam; David J. LeBlanc; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2018)

The Impact of Road Configuration in V2V-Based Cooperative Localization: Mathematical Analysis and Real-World Evaluation. - Macheng Shen; Jing Sun 003; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2018)

Accelerated Evaluation of Automated Vehicles in Car-Following Maneuvers. - Ding Zhao; Xianan Huang; Huei Peng; Henry Lam; David J. LeBlanc (IEEE Trans. Intell. Transp. Syst., 2018)

Learning and Inferring a Driver's Braking Action in Car-Following Scenarios. - Wenshuo Wang 001; Junqiang Xi; Ding Zhao (IEEE Trans. Veh. Technol., 2018)

A Learning-Based Approach for Lane Departure Warning Systems With a Personalized Driver Model. - Wenshuo Wang 001; Ding Zhao; Wei Han 005; Junqiang Xi (IEEE Trans. Veh. Technol., 2018)

Density-Adaptive Sampling for Heterogeneous Point Cloud Object Segmentation in Autonomous Vehicle Applications. - Hasan Asy'ari Arief; Mansur Arief; Manoj Bhat; Ulf Geir Indahl; Håvard Tveite; Ding Zhao (CVPR Workshops, 2019)

Streaming End-to-end Speech Recognition for Mobile Devices. - Yanzhang He; Tara N. Sainath; Rohit Prabhavalkar; Ian McGraw; Raziel Alvarez; Ding Zhao; David Rybach; Anjuli Kannan; Yonghui Wu; Ruoming Pang; Qiao Liang 001; Deepti Bhatia; et al. (ICASSP, 2019)

A Multi-Vehicle Trajectories Generator to Simulate Vehicle-to-Vehicle Encountering Scenarios. - Wenhao Ding; Wenshuo Wang 001; Ding Zhao (ICRA, 2019)

Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach. - Zuxin Liu; Mansur Arief; Ding Zhao (ICRA, 2019)

Shallow-Fusion End-to-End Contextual Biasing. - Ding Zhao; Tara N. Sainath; David Rybach; Pat Rondon; Deepti Bhatia; Bo Li 028; Ruoming Pang (INTERSPEECH, 2019)

Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field. - Yaohui Guo; Vinay Varma Kalidindi; Mansur Arief; Wenshuo Wang 001; Jiacheng Zhu; Huei Peng; Ding Zhao (ITSC, 2019)

Evaluation Uncertainty in Data-Driven Self-Driving Testing. - Zhiyuan Huang; Mansur Arief; Henry Lam; Ding Zhao (ITSC, 2019)

A General Framework of Learning Multi-Vehicle Interaction Patterns from Video. - Chengyuan Zhang 002; Jiacheng Zhu; Wenshuo Wang 001; Ding Zhao (ITSC, 2019)

Assessing Modeling Variability in Autonomous Vehicle Accelerated Evaluation. - Zhiyuan Huang; Mansur Arief; Henry Lam; Ding Zhao (CoRR, 2019)

A General Framework of Learning Multi-Vehicle Interaction Patterns from Videos. - Chengyuan Zhang 002; Jiacheng Zhu; Wenshuo Wang 001; Ding Zhao (CoRR, 2019)

Active Learning for Risk-Sensitive Inverse Reinforcement Learning. - Rui Chen 030; Wenshuo Wang 001; Zirui Zhao; Ding Zhao (CoRR, 2019)

Multi-Vehicle Interaction Scenarios Generation with Interpretable Traffic Primitives and Gaussian Process Regression. - Weiyang Zhang; Wenshuo Wang 001; Ding Zhao (CoRR, 2019)

Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process. - Jiacheng Zhu; Shenghao Qin; Wenshuo Wang 001; Ding Zhao (CoRR, 2019)

Recurrent Attentive Neural Process for Sequential Data. - Shenghao Qin; Jiacheng Zhu; Jimmy Qin; Wenshuo Wang 001; Ding Zhao (CoRR, 2019)

Destriping Algorithms Based on Statistics and Spatial Filtering for Visible-to-Thermal Infrared Pushbroom Hyperspectral Imagery. - Jianxin Jia; Yueming Wang 002; Xiaoyu Cheng; Liyin Yuan; Ding Zhao; Qi Ye; Xiaoqiong Zhuang; Rong Shu; Jianyu Wang (IEEE Trans. Geosci. Remote. Sens., 2019)

Improving Localization Accuracy in Connected Vehicle Networks Using Rao-Blackwellized Particle Filters: Theory, Simulations, and Experiments. - Macheng Shen; Jing Sun 003; Huei Peng; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2019)

Driving Style Analysis Using Primitive Driving Patterns With Bayesian Nonparametric Approaches. - Wenshuo Wang 001; Junqiang Xi; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2019)

A Streaming On-Device End-To-End Model Surpassing Server-Side Conventional Model Quality and Latency. - Tara N. Sainath; Yanzhang He; Bo Li 028; Arun Narayanan; Ruoming Pang; Antoine Bruguier; Shuo-Yiin Chang; Wei Li 133; Raziel Alvarez; Zhifeng Chen; Chung-Cheng Chiu; David Garcia; et al. (ICASSP, 2020)

CMTS: A Conditional Multiple Trajectory Synthesizer for Generating Safety-Critical Driving Scenarios. - Wenhao Ding; Mengdi Xu; Ding Zhao (ICRA, 2020)

Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method. - Wenhao Ding; Baiming Chen; Minjun Xu; Ding Zhao (IROS, 2020)

MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. - Zuxin Liu; Baiming Chen; Hongyi Zhou; Guru Koushik; Martial Hebert; Ding Zhao (IROS, 2020)

Multi-Vehicle Interaction Scenarios Generation with Interpretable Traffic Primitives and Gaussian Process Regression. - Weiyang Zhang; Wenshuo Wang 001; Jiacheng Zhu; Ding Zhao (IV, 2020)

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. - Mengdi Xu; Wenhao Ding; Jiacheng Zhu; Zuxin Liu; Baiming Chen; Ding Zhao (NeurIPS, 2020)

SAnE: Smart Annotation and Evaluation Tools for Point Cloud Data. - Hasan Asy'ari Arief; Mansur Arief; Guilin Zhang; Zuxin Liu; Manoj Bhat; Ulf Geir Indahl; Håvard Tveite; Ding Zhao (IEEE Access, 2020)

Advanced Driver Assistance Strategies for a Single-Vehicle Overtaking a Platoon on the Two-Lane Two-Way Road. - Junjie Chen; Manoj Bhat; Shiyan Jiang; Ding Zhao (IEEE Access, 2020)

Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method. - Wenhao Ding; Minjun Xu; Ding Zhao (CoRR, 2020)

A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency. - Tara N. Sainath; Yanzhang He; Bo Li 028; Arun Narayanan; Ruoming Pang; Antoine Bruguier; Shuo-Yiin Chang; Wei Li 133; Raziel Alvarez; Zhifeng Chen; Chung-Cheng Chiu; David Garcia; et al. (CoRR, 2020)

Delay-Aware Multi-Agent Reinforcement Learning. - Baiming Chen; Mengdi Xu; Zuxin Liu; Liang Li 004; Ding Zhao (CoRR, 2020)

Robust Unsupervised Learning of Temporal Dynamic Interactions. - Aritra Guha; Rayleigh Lei; Jiacheng Zhu; XuanLong Nguyen; Ding Zhao (CoRR, 2020)

Deep Probabilistic Accelerated Evaluation: A Certifiable Rare-Event Simulation Methodology for Black-Box Autonomy. - Mansur Arief; Zhiyuan Huang; Guru Koushik Senthil Kumar; Yuanlu Bai; Shengyi He; Wenhao Ding; Henry Lam; Ding Zhao (CoRR, 2020)

Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method. - Zuxin Liu; Hongyi Zhou; Baiming Chen; Sicheng Zhong; Martial Hebert; Ding Zhao (CoRR, 2020)

Clustering of Driving Encounter Scenarios Using Connected Vehicle Trajectories. - Wenshuo Wang 001; Aditya Ramesh; Jiacheng Zhu; Jie Li; Ding Zhao (IEEE Trans. Intell. Veh., 2020)

Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems. - Mansur Arief; Zhiyuan Huang; Guru Koushik Senthil Kumar; Yuanlu Bai; Shengyi He; Wenhao Ding; Henry Lam; Ding Zhao (AISTATS, 2021)

Dynamic Sparsity Neural Networks for Automatic Speech Recognition. - Zhaofeng Wu; Ding Zhao; Qiao Liang 001; Jiahui Yu; Anmol Gulati; Ruoming Pang (ICASSP, 2021)

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. - Baiming Chen; Zuxin Liu; Jiacheng Zhu; Mengdi Xu; Wenhao Ding; Liang Li 004; Ding Zhao (ICRA, 2021)

Personalized Keyphrase Detection Using Speaker and Environment Information. - Rajeev Rikhye; Quan Wang; Qiao Liang 001; Yanzhang He; Ding Zhao; Yiteng Huang; Arun Narayanan; Ian McGraw (Interspeech, 2021)

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. - Baiming Chen; Zuxin Liu; Jiacheng Zhu; Mengdi Xu; Wenhao Ding; Ding Zhao (CoRR, 2021)

Functional Optimal Transport: Mapping Estimation and Domain Adaptation for Functional data. - Jiacheng Zhu; Aritra Guha; Mengdi Xu; Yingchen Ma; Rayleigh Lei; Vincenzo Loffredo; XuanLong Nguyen; Ding Zhao (CoRR, 2021)

Improving Perception via Sensor Placement: Designing Multi-LiDAR Systems for Autonomous Vehicles. - Sharad Chitlangia; Zuxin Liu; Akhil Agnihotri; Ding Zhao (CoRR, 2021)

Semantically Controllable Scene Generation with Guidance of Explicit Knowledge. - Wenhao Ding; Bo Li 026; Kim Ji Eun; Ding Zhao (CoRR, 2021)

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)

CausalAF: Causal Autoregressive Flow for Goal-Directed Safety-Critical Scenes Generation. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (CoRR, 2021)

Delay-aware model-based reinforcement learning for continuous control. - Baiming Chen; Mengdi Xu; Liang Li 004; Ding Zhao (Neurocomputing, 2021)

Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation. - Wenhao Ding; Baiming Chen; Bo Li 026; Kim Ji Eun; Ding Zhao (IEEE Robotics Autom. Lett., 2021)

Highway Exiting Planner for Automated Vehicles Using Reinforcement Learning. - Zhong Cao; Diange Yang; Shaobing Xu; Huei Peng; Boqi Li 001; Shuo Feng 002; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2021)

How to Evaluate Proving Grounds for Self-Driving? A Quantitative Approach. - Rui Chen 030; Mansur Arief; Weiyang Zhang; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2021)

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression. - Jiacheng Zhu; Gregory Darnell; Agni Kumar; Ding Zhao; Bo Li 026; XuanLong Nguyen; Shirley You Ren (CHIL, 2022)

CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (CoRL, 2022)

Robustness Certification of Visual Perception Models via Camera Motion Smoothing. - Hanjiang Hu; Zuxin Liu; Linyi Li 001; Jiacheng Zhu; Ding Zhao (CoRL, 2022)

Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving. - Hanjiang Hu; Zuxin Liu; Sharad Chitlangia; Akhil Agnihotri; Ding Zhao (CVPR, 2022)

COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks. - Fan Wu 011; Linyi Li 001; Huan Zhang 001; Bhavya Kailkhura; Krishnaram Kenthapadi; Ding Zhao; Bo Li 026 (ICLR, 2022)

CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing. - Fan Wu 011; Linyi Li 001; Zijian Huang 002; Yevgeniy Vorobeychik; Ding Zhao; Bo Li 026 (ICLR, 2022)

Constrained Variational Policy Optimization for Safe Reinforcement Learning. - Zuxin Liu; Zhepeng Cen; Vladislav Isenbaev; Wei Liu; Zhiwei Steven Wu; Bo Li 026; Ding Zhao (ICML, 2022)

Prompting Decision Transformer for Few-Shot Policy Generalization. - Mengdi Xu; Yikang Shen; Shun Zhang; Yuchen Lu; Ding Zhao; Joshua B. Tenenbaum; Chuang Gan 001 (ICML, 2022)

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

A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes. - Shaojin Ding; Weiran Wang; Ding Zhao; Tara N. Sainath; Yanzhang He; Robert David; Rami Botros; Xin Wang 016; Rina Panigrahy; Qiao Liang 001; Dongseong Hwang; Ian McGraw; et al. (INTERSPEECH, 2022)

Federated Pruning: Improving Neural Network Efficiency with Federated Learning. - Rongmei Lin; Yonghui Xiao; Tien-Ju Yang; Ding Zhao; Li Xiong 001; Giovanni Motta; Françoise Beaufays (INTERSPEECH, 2022)

Improve Speech Enhancement using Perception-High-Related Time-Frequency Loss. - Ding Zhao; Zhan Zhang; Bin Yu; Yuehai Wang (INTERSPEECH, 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)

Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS). - Mansur Arief; Zhepeng Cen; Zhenyuan Liu; Zhiyuan Huang; Bo Li 026; Henry Lam; Ding Zhao (ITSC, 2022)

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

Road Traffic Law Adaptive Decision-making for Self-Driving Vehicles. - Jiaxin Lin; Wenhui Zhou; Hong Wang 014; Zhong Cao; Wenhao Yu 006; Chengxiang Zhao; Ding Zhao; Diange Yang; Jun Li 082 (ITSC, 2022)

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction. - Jiacheng Zhu; Jielin Qiu; Zhuolin Yang; Douglas Weber; Michael A. Rosenberg; Emerson Liu; Bo Li 026; Ding Zhao (MLHC, 2022)

Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (NeurIPS, 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)

SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles. - Chejian Xu; Wenhao Ding; Weijie Lyu; Zuxin Liu; Shuai Wang; Yihan He; Hanjiang Hu; Ding Zhao; Bo Li 026 (NeurIPS, 2022)

Joint Transmit and Reflective Beamforming for IRS-Assisted Integrated Sensing and Communication. - Xianxin Song; Ding Zhao; Haocheng Hua; Tony Xiao Han; Xun Yang 009; Jie Xu 002 (WCNC, 2022)

Optimal Transport based Data Augmentation for Heart Disease Diagnosis and Prediction. - Jielin Qiu; Jiacheng Zhu; Michael A. Rosenberg; Emerson Liu; Ding Zhao (CoRR, 2022)

COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks. - Fan Wu 011; Linyi Li 001; Chejian Xu; Huan Zhang 001; Bhavya Kailkhura; Krishnaram Kenthapadi; Ding Zhao; Bo Li 026 (CoRR, 2022)

Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling. - Mansur Arief; Zhepeng Cen; Zhenyuan Liu; Zhiyuan Huang; Henry Lam; Bo Li 026; Ding Zhao (CoRR, 2022)

MHMS: Multimodal Hierarchical Multimedia Summarization. - Jielin Qiu; Jiacheng Zhu; Mengdi Xu; Franck Dernoncourt; Trung Bui; Zhaowen Wang; Bo Li 026; Ding Zhao; Hailin Jin (CoRR, 2022)

Road Traffic Law Adaptive Decision-making for Self-Driving Vehicles. - Jiaxin Liu; Wenhui Zhou; Hong Wang 014; Zhong Cao; Wenhao Yu 006; Chengxiang Zhao; Ding Zhao; Diange Yang; Jun Li 082 (CoRR, 2022)

An Empirical Exploration of Cross-domain Alignment between Language and Electroencephalogram. - William Han; Jielin Qiu; Jiacheng Zhu; Mengdi Xu; Douglas Weber; Bo Li 026; Ding Zhao (CoRR, 2022)

Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions. - Chulin Xie; Zhong Cao; Yunhui Long; Diange Yang; Ding Zhao; Bo Li 026 (CoRR, 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)

Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment. - Jielin Qiu; Jiacheng Zhu; Mengdi Xu; Franck Dernoncourt; Trung Bui; Zhaowen Wang; Bo Li 026; Ding Zhao; Hailin Jin (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)

Digitization of Chinese Traffic Laws: Methodologies, Quantative Analysis, and Usage for Monitoring Driving Compliance. - Wenhao Yu 006; Chengxiang Zhao; Jiaxin Liu; Yingkai Yang; Xiaohan Ma; Jun Li 082; Weida Wang; Hong Wang 014; Ding Zhao (CoRR, 2022)

Are Multimodal Models Robust to Image and Text Perturbations? - Jielin Qiu; Yi Zhu 001; Xingjian Shi; Florian Wenzel; Zhiqiang Tang 001; Ding Zhao; Bo Li 026; Mu Li 003 (CoRR, 2022)

Guest Editorial Special Issue on Artificial Intelligence for Autonomous Unmanned System Applications. - Hongbo Gao 001; Ming Liu 001; Fei Chen 007; Xiaoxiang Na; Ding Zhao; Jingtao Wang; Linghe Kong; Keqiang Li; Chun-Yi Su (IEEE Trans Autom. Sci. Eng., 2022)

Understanding V2V Driving Scenarios Through Traffic Primitives. - Wenshuo Wang 001; Weiyang Zhang; Jiacheng Zhu; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2022)

Rare-event Simulation for Neural Network and Random Forest Predictors. - Yuanlu Bai; Zhiyuan Huang; Henry Lam; Ding Zhao (ACM Trans. Model. Comput. Simul., 2022)

SCCS: Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment. - Jielin Qiu; Jiacheng Zhu; Mengdi Xu; Franck Dernoncourt; Trung Bui; Zhaowen Wang; Bo Li 026; Ding Zhao; Hailin Jin (ACL (Findings), 2023)

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)

Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models? - Jielin Qiu; William Han; Jiacheng Zhu; Mengdi Xu; Michael A. Rosenberg; Emerson Liu; Douglas Weber; Ding Zhao (EACL (Findings), 2023)

Can Brain Signals Reveal Inner Alignment with Human Languages? - Jielin Qiu; William Han; Jiacheng Zhu; Mengdi Xu; Douglas Weber; Bo Li 026; Ding Zhao (EMNLP (Findings), 2023)

Structured Two-Stage True-Time-Delay Array Code book Design for Multi - User Data Communication. - Aditya Wadaskar; Ding Zhao; Ibrahim Pehlivan; Danijela Cabric (GLOBECOM, 2023)

Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Models. - Steven M. Hernandez; Ding Zhao; Shaojin Ding; Antoine Bruguier; Rohit Prabhavalkar; Tara N. Sainath; Yanzhang He; Ian McGraw (ICASSP, 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)

Multi-Output RNN-T Joint Networks for Multi-Task Learning of ASR and Auxiliary Tasks. - Weiran Wang; Ding Zhao; Shaojin Ding; Hao Zhang 010; Shuo-Yiin Chang; David Rybach; Tara N. Sainath; Yanzhang He; Ian McGraw; Shankar Kumar (ICASSP, 2023)

On the Robustness of Safe Reinforcement Learning under Observational Perturbations. - Zuxin Liu; Zijian Guo 002; Zhepeng Cen; Huan Zhang 001; Jie Tan 001; Bo Li 026; Ding Zhao (ICLR, 2023)

Hyper-Decision Transformer for Efficient Online Policy Adaptation. - Mengdi Xu; Yuchen Lu; Yikang Shen; Shun Zhang; Ding Zhao; Chuang Gan 001 (ICLR, 2023)

Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models. - Wenhao Ding; Tong Che; Ding Zhao; Marco Pavone 001 (ICML, 2023)

Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data. - Zuxin Liu; Zijian Guo 002; Zhepeng Cen; Huan Zhang 001; Yihang Yao; Hanjiang Hu; Ding Zhao (ICML, 2023)

Constrained Decision Transformer for Offline Safe Reinforcement Learning. - Zuxin Liu; Zijian Guo 002; Yihang Yao; Zhepeng Cen; Wenhao Yu 003; Tingnan Zhang; Ding Zhao (ICML, 2023)

Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics. - Jiacheng Zhu; Jielin Qiu; Aritra Guha; Zhuolin Yang; XuanLong Nguyen; Bo Li 026; Ding Zhao (ICML, 2023)

Learning to View: Decision Transformers for Active Object Detection. - Wenhao Ding; Nathalie Majcherczyk; Mohit Deshpande; Xuewei Qi; Ding Zhao; Rajasimman Madhivanan; Arnie Sen (ICRA, 2023)

SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark Under Multiple Environments. - Hanjiang Hu; Baoquan Yang; Zhijian Qiao; Shiqi Liu 005; Jiacheng Zhu; Zuxin Liu; Wenhao Ding; Ding Zhao; Hesheng Wang 001 (IROS, 2023)

GOATS: Goal Sampling Adaptation for Scooping with Curriculum Reinforcement Learning. - Yaru Niu; Shiyu Jin; Zeqing Zhang; Jiacheng Zhu; Ding Zhao; Liangjun Zhang (IROS, 2023)

Digitization of Traffic Laws: Methodologies and Usage for Monitoring Driving Compliance. - Chengxiang Zhao; Wenhao Yu 003; Xiaohan Ma; Yuzhuang Zhao; Boqi Li 001; Weida Wang; Jia Hu 003; Hong Wang 007; Ding Zhao (ITSC, 2023)

Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report. - Jielin Qiu; Jiacheng Zhu; Shiqi Liu 005; William Han; Jingqi Zhang; Chaojing Duan; Michael A. Rosenberg; Emerson Liu; Douglas Weber; Ding Zhao (ML4H@NeurIPS, 2023)

Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision. - Makiya Nakashima; Donna Salem; W. H. Wilson Tang; Christopher Nguyen; Tae-Hyun Hwang; Ding Zhao; Byung-Hak Kim; Deborah Kwon; David Chen 006 (MLHC, 2023)

Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. - Wenhao Ding; Laixi Shi; Yuejie Chi; Ding Zhao (NeurIPS, 2023)

Learning Shared Safety Constraints from Multi-task Demonstrations. - Konwoo Kim; Gokul Swamy; Zuxin Liu; Ding Zhao; Sanjiban Choudhury; Zhiwei Steven Wu (NeurIPS, 2023)

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. - Yihang Yao; Zuxin Liu; Zhepeng Cen; Jiacheng Zhu; Wenhao Yu 003; Tingnan Zhang; Ding Zhao (NeurIPS, 2023)

LiveSeg: Unsupervised Multimodal Temporal Segmentation of Long Livestream Videos. - Jielin Qiu; Franck Dernoncourt; Trung Bui; Zhaowen Wang; Ding Zhao; Hailin Jin (WACV, 2023)

Interpolation for Robust Learning: Data Augmentation on Geodesics. - Jiacheng Zhu; Jielin Qiu; Aritra Guha; Zhuolin Yang; XuanLong Nguyen; Bo Li 026; Ding Zhao (CoRR, 2023)

Converting ECG Signals to Images for Efficient Image-text Retrieval via Encoding. - Jielin Qiu; Jiacheng Zhu; Shiqi Liu 005; William Han; Jingqi Zhang; Chaojing Duan; Michael A. Rosenberg; Emerson Liu; Douglas Weber; Ding Zhao (CoRR, 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)

MultiSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos. - Jielin Qiu; Jiacheng Zhu; William Han; Aditesh Kumar; Karthik Mittal; Claire Jin; Zhengyuan Yang; Linjie Li; Jianfeng Wang; Bo Li 026; Ding Zhao; Lijuan Wang (CoRR, 2023)

Your Room is not Private: Gradient Inversion Attack for Deep Q-Learning. - Miao Li; Wenhao Ding; Ding Zhao (CoRR, 2023)

Datasets and Benchmarks for Offline Safe Reinforcement Learning. - Zuxin Liu; Zijian Guo 002; Haohong Lin; Yihang Yao; Jiacheng Zhu; Zhepeng Cen; Hanjiang Hu; Wenhao Yu 003; Tingnan Zhang; Jie Tan 001; Ding Zhao (CoRR, 2023)

The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation. - Lingdong Kong; Yaru Niu; Shaoyuan Xie; Hanjiang Hu; Lai Xing Ng; Benoit R. Cottereau; Ding Zhao; Liangjun Zhang; Hesheng Wang 001; Wei Tsang Ooi; Ruijie Zhu 002; Ziyang Song; et al. (CoRR, 2023)

Contextual Biasing with the Knuth-Morris-Pratt Matching Algorithm. - Weiran Wang; Zelin Wu; Diamantino Caseiro; Tsendsuren Munkhdalai; Khe Chai Sim; Pat Rondon; Golan Pundak; Gan Song; Rohit Prabhavalkar; Zhong Meng; Ding Zhao; Tara N. Sainath; et al. (CoRR, 2023)

Guardians as You Fall: Active Mode Transition for Safe Falling. - Yikai Wang; Mengdi Xu; Guanya Shi; Ding Zhao (CoRR, 2023)

Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. - Ye Li; Hanjiang Hu; Zuxin Liu; Ding Zhao (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)

Safety-aware Causal Representation for Trustworthy Reinforcement Learning in Autonomous Driving. - Haohong Lin; Wenhao Ding; Zuxin Liu; Yaru Niu; Jiacheng Zhu; Yuming Niu; Ding Zhao (CoRR, 2023)

A Survey on Safety-Critical Driving Scenario Generation - A Methodological Perspective. - Wenhao Ding; Chejian Xu; Mansur Arief; Haohong Lin; Bo Li 026; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2023)

Semantic Traffic Law Adaptive Decision-Making for Self-Driving Vehicles. - Jiaxin Liu; Hong Wang 014; Zhong Cao; Wenhao Yu 006; Chengxiang Zhao; Ding Zhao; Diange Yang; Jun Li 082 (IEEE Trans. Intell. Transp. Syst., 2023)

Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations. - Hanjiang Hu; Zuxin Liu; Linyi Li 001; Jiacheng Zhu; Ding Zhao (AISTATS, 2024)

Interpretation of Intracardiac Electrograms Through Textual Representations. - William Han; Diana Guadalupe Gomez; Avi Alok; Chaojing Duan; Michael A. Rosenberg; Douglas Weber; Emerson Liu; Ding Zhao (CHIL, 2024)

MMSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos. - Jielin Qiu; Jiacheng Zhu; William Han; Aditesh Kumar; Karthik Mittal; Claire Jin; Zhengyuan Yang; Linjie Li; Jianfeng Wang; Ding Zhao; Bo Li 026; Lijuan Wang (CVPR, 2024)

RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios. - Wenhao Ding; Yulong Cao; Ding Zhao; Chaowei Xiao; Marco Pavone 001 (ECCV (62), 2024)

Fast Frequency-Direction Mapping Design for Data Communication With True-Time-Delay Array Architecture. - Ding Zhao; Ibrahim Pehlivan; Aditya Wadaskar; Danijela Cabric (ICNC, 2024)

Learning from Sparse Offline Datasets via Conservative Density Estimation. - Zhepeng Cen; Zuxin Liu; Zitong Wang 005; Yihang Yao; Henry Lam; Ding Zhao (ICLR, 2024)

Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer. - Xingyu Liu 001; Deepak Pathak; Ding Zhao (ICLR, 2024)

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. - Zuxin Liu; Jesse Zhang; Kavosh Asadi; Yao Liu 009; Ding Zhao; Shoham Sabach; Rasool Fakoor (ICLR, 2024)

Feasibility Consistent Representation Learning for Safe Reinforcement Learning. - Zhepeng Cen; Yihang Yao; Zuxin Liu; Ding Zhao (ICML, 2024)

Privacy Risks in Reinforcement Learning for Household Robots. - Miao Li; Wenhao Ding; Ding Zhao (ICRA, 2024)

Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. - Ye Li; Hanjiang Hu; Zuxin Liu; Xiaohao Xu; Xiaonan Huang; Ding Zhao (ICRA, 2024)

Generalize by Touching: Tactile Ensemble Skill Transfer for Robotic Furniture Assembly. - Haohong Lin; Radu Corcodel; Ding Zhao (ICRA, 2024)

Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization. - Fan Yang; Wenxuan Zhou; Zuxin Liu; Ding Zhao; David Held (ICRA, 2024)

COMPOSER: Scalable and Robust Modular Policies for Snake Robots. - Yuyou Zhang; Yaru Niu; Xingyu Liu 001; Ding Zhao (ICRA, 2024)

Contextual Biasing with the Knuth-Morris-Pratt Matching Algorithm. - Weiran Wang; Zelin Wu; Diamantino Caseiro; Tsendsuren Munkhdalai; Khe Chai Sim; Pat Rondon; Golan Pundak; Gan Song; Rohit Prabhavalkar; Zhong Meng; Ding Zhao; Tara Sainath; et al. (INTERSPEECH, 2024)

LocoMan: Advancing Versatile Quadrupedal Dexterity with Lightweight Loco-Manipulators. - Changyi Lin; Xingyu Liu 001; Yuxiang Yang 007; Yaru Niu; Wenhao Yu 003; Tingnan Zhang; Jie Tan 001; Byron Boots; Ding Zhao (IROS, 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)

Embodied Executable Policy Learning with Language-based Scene Summarization. - Jielin Qiu; Mengdi Xu; William Han; Seungwhan Moon; Ding Zhao (NAACL-HLT, 2024)

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning. - Haohong Lin; Wenhao Ding; Jian Chen; Laixi Shi; Jiacheng Zhu; Bo Li; Ding Zhao (NeurIPS, 2024)

OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning. - Yihang Yao; Zhepeng Cen; Wenhao Ding; Haohong Lin; Shiqi Liu 005; Tingnan Zhang; Wenhao Yu 003; Ding Zhao (NeurIPS, 2024)

Design and Control Co-Optimization for Automated Design Iteration of Dexterous Anthropomorphic Soft Robotic Hands. - Pragna Mannam; Xingyu Liu 001; Ding Zhao; Jean Oh; Nancy S. Pollard (RoboSoft, 2024)

Interpretation of Intracardiac Electrograms Through Textual Representations. - William Jongwon Han; Diana Gómez; Avi Alok; Chaojing Duan; Michael A. Rosenberg; Douglas Weber; Emerson Liu; Ding Zhao (CoRR, 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)

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. - David Dalrymple; Joar Skalse; Yoshua Bengio; Stuart Russell 001; Max Tegmark; Sanjit Seshia; Steve Omohundro; Christian Szegedy; Ben Goldhaber; Nora Ammann; Alessandro Abate; Joe Halpern; et al. (CoRR, 2024)

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning. - Haohong Lin; Wenhao Ding; Jian Chen; Laixi Shi; Jiacheng Zhu; Bo Li 026; Ding Zhao (CoRR, 2024)

Agile Continuous Jumping in Discontinuous Terrains. - Yuxiang Yang 007; Guanya Shi; Changyi Lin; Xiangyun Meng; Rosario Scalise; Mateo Guaman Castro; Wenhao Yu 003; Tingnan Zhang; Ding Zhao; Jie Tan 001; Byron Boots (CoRR, 2024)

DTactive: A Vision-Based Tactile Sensor with Active Surface. - Jikai Xu; Lei Wu; Changyi Lin; Ding Zhao; Huazhe Xu (CoRR, 2024)

Learning Multi-Agent Loco-Manipulation for Long-Horizon Quadrupedal Pushing. - Yuming Feng; Chuye Hong; Yaru Niu; Shiqi Liu 005; Yuxiang Yang 007; Wenhao Yu 003; Tingnan Zhang; Jie Tan 001; Ding Zhao (CoRR, 2024)

ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling. - William Han; Chaojing Duan; Michael A. Rosenberg; Emerson Liu; Ding Zhao (CoRR, 2024)

Causal Composition Diffusion Model for Closed-loop Traffic Generation. - Haohong Lin; Xin Huang; Tung Phan-Minh; David S. Hayden; Huan Zhang 001; Ding Zhao; Siddhartha S. Srinivasa; Eric M. Wolff; Hongge Chen (CoRR, 2024)

Overconservativeness of Variance-Based Efficiency Criteria and Probabilistic Efficiency in Rare-Event Simulation. - Yuanlu Bai; Zhiyuan Huang; Henry Lam; Ding Zhao (Manag. Sci., 2024)

Liquid Hydrogen Temperature Cryostage for Ice-Assisted Electron-Beam Lithography. - Rui Zheng; Limin Qi; Sizhuo Li; Zhihua Gan; Ding Zhao; Min Qiu (IEEE Trans. Instrum. Meas., 2024)

Lab-on-Fiber Fabry-Perot Interferometer Integrated With Functionalized Polymer for Carbon Dioxide Sensing. - Rujun Zhou; Lei Zhang; Yunlian Ding; Si Luo; Qiang Ling 003; Yao Chen; Yusheng Zhang; Yan Zhou; Ali Akhtar; Ding Zhao; Min Qiu; Daru Chen (IEEE Trans. Instrum. Meas., 2024)

Safety-Aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving. - Haohong Lin; Wenhao Ding; Zuxin Liu; Yaru Niu; Jiacheng Zhu; Yuming Niu; Ding Zhao (IEEE Robotics Autom. Lett., 2024)

DiffScene: Diffusion-Based Safety-Critical Scenario Generation for Autonomous Vehicles. - Chejian Xu; Aleksandr Petiushko; Ding Zhao; Bo Li (AAAI, 2025)

Your Language Model May Think Too Rigidly: Achieving Reasoning Consistency with Symmetry-Enhanced Training. - Yihang Yao; Zhepeng Cen; Miao Li; William Han; Yuyou Zhang; Emerson Liu; Zuxin Liu; Chuang Gan 001; Ding Zhao (ACL (Findings), 2025)

Safety is Not Only About Refusal: Reasoning-Enhanced Fine-tuning for Interpretable LLM Safety. - Yuyou Zhang; Miao Li; William Han; Yihang Yao; Zhepeng Cen; Ding Zhao (ACL (Findings), 2025)

Causal Composition Diffusion Model for Closed-loop Traffic Generation. - Haohong Lin; Xin Huang; Tung Phan; David S. Hayden; Huan Zhang 001; Ding Zhao; Siddhartha S. Srinivasa; Eric M. Wolff; Hongge Chen (CVPR, 2025)

SatPipe: Deterministic TCP Adaptation for Highly Dynamic LEO Satellite Networks. - Ding Zhao; Xinyu Zhang; Myungjin Lee (INFOCOM, 2025)

MONA: Moving Object Detection from Videos Shot by Dynamic Camera. - Boxun Hu; Mingze Xia; Ding Zhao; Guanlin Wu (CoRR, 2025)

Semantically Adversarial Scene Generation With Explicit Knowledge Guidance. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2025)

QuietPaw: Learning Quadrupedal Locomotion with Versatile Noise Preference Alignment. - Yuyou Zhang; Yihang Yao; Shiqi Liu; Yaru Niu; Changyi Lin; Yuxiang Yang; Wenhao Yu 003; Tingnan Zhang; Jie Tan 001; Ding Zhao (CoRR, 2025)

Feature-EndoGaussian: Feature Distilled Gaussian Splatting in Surgical Deformable Scene Reconstruction. - Kai Li; Junhao Wang; William Han; Ding Zhao (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)

CrashAgent: Crash Scenario Generation via Multi-modal Reasoning. - Miao Li; Wenhao Ding; Haohong Lin; Yiqi Lyu; Yihang Yao; Yuyou Zhang; Ding Zhao (CoRR, 2025)

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework. - William Han; Chaojing Duan; Zhepeng Cen; Yihang Yao; Xiaoyu Song; Atharva Mhaskar; Dylan Leong; Michael A. Rosenberg; Emerson Liu; Ding Zhao (CoRR, 2025)

Behavior Injection: Preparing Language Models for Reinforcement Learning. - Zhepeng Cen; Yihang Yao; William Han; Zuxin Liu; Ding Zhao (CoRR, 2025)

LocoTouch: Learning Dexterous Quadrupedal Transport with Tactile Sensing. - Changyi Lin; Yuxin Ray Song; Boda Huo; Mingyang Yu; Yikai Wang; Shiqi Liu; Yuxiang Yang; Wenhao Yu 003; Tingnan Zhang; Jie Tan 001; Yiyue Luo; Ding Zhao (CoRR, 2025)

Human2LocoMan: Learning Versatile Quadrupedal Manipulation with Human Pretraining. - Yaru Niu; Yunzhe Zhang; Mingyang Yu; Changyi Lin; Chenhao Li; Yikai Wang; Yuxiang Yang 007; Wenhao Yu 003; Tingnan Zhang; Bingqing Chen; Jonathan Francis; Zhenzhen Li; et al. (CoRR, 2025)

Bipedalism for Quadrupedal Robots: Versatile Loco-Manipulation through Risk-Adaptive Reinforcement Learning. - Yuyou Zhang; Radu Corcodel; Ding Zhao (CoRR, 2025)