Physical AI · Autonomous systems · Safety · Robot learning
Sushant Veer
Senior Research Scientist
NVIDIA Autonomous Systems and Physical AI Research (ASPIRE) Group
I develop methods for evaluating and improving the safety and robustness of learning-based autonomous systems.
My research brings together generative world models, reasoning vision-language models (VLMs), statistical learning, and control, with applications in autonomous driving and robotics.
Publications
Journal articles, conference papers, and work in progress. View Google Scholar
Preprints 08
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Coverage Aware Active Evaluation for Failure Discovery with Paired Systems
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X4Val: Learning Neural Surrogates for Variance-Reduced Policy Evaluation
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StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement
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The Case for Negative Data: From Crash Reports to Counterfactuals for Reasonable Driving
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RealDrive: Retrieval-Augmented Driving with Diffusion Models
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Surprise Potential as a Measure of Interactivity in Driving Scenarios
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HT-LIP Model Based Robust Control of Quadrupedal Robot Locomotion under Unknown Vertical Ground Motion
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Learning Provably Robust Motion Planners Using Funnel Libraries
Journal articles 09
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Safety Evaluation of Motion Plans Using Trajectory Predictors as Forward Reachable Set Estimators
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Task-Driven Detection of Distribution Shifts With Statistical Guarantees for Robot Learning
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Wolf: Dense Video Captioning with a World Summarization Framework
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Interactive Joint Planning for Autonomous Vehicles
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Analytical Solution to a Time-Varying LIP Model for Quadrupedal Walking on a Vertically Oscillating Surface
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Interactive Dynamic Walking: Learning Gait Switching Policies with Generalization Guarantees
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Switched Systems with Multiple Equilibria Under Disturbances: Boundedness and Practical Stability
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Input-to-State Stability of Periodic Orbits of Systems with Impulse Effects via Poincaré Analysis
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Approximate Spring Balancing of Linkages to Reduce Actuator Requirements
Conference papers 33
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Modular Safety Guardrails Are Necessary for Foundation-Model-Enabled Robots in the Real World
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Sim2Val: Leveraging Correlation Across Test Platforms for Variance-Reduced Metric Estimation
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Online Aggregation of Trajectory Predictors
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LoRD: Adapting Differentiable Driving Policies to Distribution Shifts
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System-Level Safety Monitoring and Recovery for Perception Failures in Autonomous Vehicles
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Driving Everywhere with Large Language Model Policy Adaptation
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RuleFuser: An Evidential Bayes Approach for Rule Injection in Imitation Learned Planners and Predictors for Robustness under Distribution Shifts
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Multi-Predictor Fusion: Combining Learning-based and Rule-based Trajectory Predictors
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PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction
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Task-Aware Risk Estimation of Perception Failures for Autonomous Vehicles
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Receding Horizon Planning with Rule Hierarchies for Autonomous Vehicles
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Guided Conditional Diffusion for Controllable Traffic Simulation
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Learning Autonomous Vehicle Safety Concepts from Demonstrations
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Asymptotic Stabilization of Aperiodic Trajectories of a Hybrid-Linear Inverted Pendulum Walking on a Vertically Moving Surface
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Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles
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Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data
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Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning
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Probably Approximately Correct Vision-Based Planning using Motion Primitives
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Generalization Guarantees for Imitation Learning
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LagNetViP: A Lagrangian Neural Network for Video Prediction
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An Adaptive Supervisory Control Approach to Dynamic Locomotion Under Parametric Uncertainty
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Robustness of Periodic Orbits of Impulsive Systems à la Poincaré
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PD based Robust Quadratic Programs for Robotic Systems
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Safe Adaptive Switching among Dynamical Movement Primitives: Application to 3D Limit-Cycle Walkers
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Practical Stability of Switched Systems With Multiple Equilibria Under Disturbances
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Generation of and Switching among Limit-Cycle Bipedal Walking Gaits
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Adaptation of Limit-Cycle Walkers for Collaborative Tasks: A Supervisory Switching Control Approach
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Almost Driftless Navigation of 3D Limit-Cycle Walking Bipeds
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Steering a 3D Limit-Cycle Walker for Collaboration with a Leader
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Composing Limit Cycles for Motion Planning of 3D Bipedal Walkers
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Local Input-to-State Stability of Dynamic Walking Under Persistent External Excitation using Hybrid Zero Dynamics
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Integrating Dynamic Walking and Arm Impedance Control for Cooperative Transportation
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On the Adaptation of Dynamic Walking to Persistent External Forcing using Hybrid Zero Dynamics Control
Patents 09
Granted patents
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Learning autonomous vehicle safety concepts from demonstrations
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Task-relevant failure detection for trajectory prediction in machines
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A Semi-Flexion Orthotic Knee
Patent applications
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Techniques for Controlling Autonomous Vehicles Using Vision-Language Models
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Techniques for Adaptive Driving Using Language Models
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Operating Law Aware Planning Criteria for Intelligent Machines and Neural Motion Planners Integrated with the Planning Criteria
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Interactive Motion Planning for Autonomous Systems and Applications
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Techniques for Combining Learning-Based and Rule-Based Model Predictions
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Ego Trajectory Planning with Rule Hierarchies for Autonomous Vehicles
Posters & presentations 03
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Physical Collaboration between Dynamically Walking Bipedal Robots and Humans
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Integration of Dynamic Walking with Arm Impedance Control for Safe Physical Human-Biped Collaboration
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Design of A Standing Wheelchair
Education & training
- 2018–2021
Postdoctoral Research Associate
Mechanical and Aerospace Engineering
Advisor: Prof. Anirudha Majumdar
Princeton University - 2013–2018
Ph.D. in Mechanical Engineering
Advisor: Prof. Ioannis Poulakakis - 2009–2013
B.Tech. in Mechanical Engineering
Indian Institute of Technology Madras
Advisor: Prof. Sujatha Srinivasan