Research
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Current Projects

Human-centered Action recognition and Prediction
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Hardware, control and perception for robust manipulation in cluttered environments
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Learning to interact with articulated objects
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Model Predictive Control for Safe Limit Driving in Highly Dynamic Environments
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Joint Contextual Forecasting of Vehicle Behaviors, Actions, and Trajectories
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Safe Feedback Interactions in Human-Autonomous Vehicle Systems
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Exploiting Depth and Motion Cues for Robust Semantic, Instance-level Segmentation and Tracking
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Dexterity and Perception Enhancement for Robots
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Robust and Interpretable Machine Learning via Natural Language Explanations
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Data-Driven Analysis of Multi-Modal Sensory Inputs for the Design of Smart Environments
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A Macroscope for Fleets of Intelligent Vehicles
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Joint Contextual Forecasting of Vehicle Behaviors, Actions, and Trajectories
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