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Research

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Current Projects

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Intelligent Testing with Interpretable and High-Capacity Agents by Embedding Logical Structure in Neural Architectures

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Human-centered Action recognition and Prediction

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Autonomous Drifting: Demonstrating a Reciprocal Architecture for Motion Planning and Control

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Planning Set-Based Trajectory Envelops in Dynamic Driving Environments for Guaranteed-Safe Guardian Autonomy

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Hardware, control and perception for robust manipulation in cluttered environments

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Leveraging Language for Generalizable, Composable, and Interactive Robot Learning

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Learning Traffic Screenplays through 3D Object Detection and Tracking

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Learning to interact with articulated objects

Collaboration with CMU

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Physical and Functional Inductive Biases for Visual Representation Learning

Physical and Functional Inductive Biases for Visual Representation Learning

Collaboration with MIT

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Completed Projects

Two-Hand Robotic Manipulation Skills

Two-Hand Robotic Manipulation Skills

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Model Predictive Control for Safe Limit Driving in Highly Dynamic Environments

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Supersizing Robot Learning through Hybrid Imitation

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Joint Contextual Forecasting of Vehicle Behaviors, Actions, and Trajectories

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A Model Guardian to Enforce and Improve Intelligent Vehicle Safety

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Individual Driving Styles: Learning, Modeling, and Improving Driver Safety

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Safe Feedback Interactions in Human-Autonomous Vehicle Systems

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An Engagement Learning Approach to Generating Massive Labeled Datasets for Training AI Systems

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Cloud-Aided Computer Vision for Autonomous Devices

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Exploiting Depth and Motion Cues for Robust Semantic, Instance-level Segmentation and Tracking

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Acquiring, Representing, and Transporting Manipulation Knowledge

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Soft Robotics and Haptics for Shared Autonomy and Teleoperation

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Dexterity and Perception Enhancement for Robots

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Emergent Behaviors in Multi-Agent Human-Robot Teams

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Interaction-Aware Control for Cars that Anticipate and Explain Complex Environments

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Robust and Interpretable Machine Learning via Natural Language Explanations

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Hands and Sensors for Robots That Can Do Dishes

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Data-efficient Algorithms for Machine Learning with Provable Guarantees

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Data-Driven Analysis of Multi-Modal Sensory Inputs for the Design of Smart Environments

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Closing the Visual-Motor Loop with Deep Reinforcement Learning

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A Macroscope for Fleets of Intelligent Vehicles

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Dynamic Choice Models of Human Decision-Making

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Rich Physical Human/Robot Interaction Skills in Versatile Real/Life Scenarios

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Joint Contextual Forecasting of Vehicle Behaviors, Actions, and Trajectories

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Uncertainty on Uncertainty, Robustness, and Simulation

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Human-Centric Autonomous and Assistive Driving

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Understanding Driver State in Laboratory and Naturalistic Environments

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Human Behaviors and Interaction for In-Car Experiences

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