Rethinking Robot Safety: Adaptive and Scalable Methods for Real-World Autonomy
Abstract: Safe autonomy in the real world requires more than safety in structured, low-dimensional settings. Robots deployed in everyday environments must cope with non-stationarity—objectives and dynamics that change due to human preferences or evolving operating conditions—and must also scale safety reasoning to high-dimensional robots and environments, where perception, dynamics, and safety constraints can be complex [...]
Empirically Grounded LLM-based Virtual Patients for Psychotherapy Training: Design, Modeling, and Evaluation
Abstract: The need for mental health care continues to outpace the supply of trained psychotherapists, while psychotherapy training remains constrained by limited supervision time and scarce opportunities for repeated, feedback-rich practice in realistic scenarios. Simulation-based training can mitigate these constraints, but actor-based standardized patients are costly and difficult to scale, and many clinically challenging moments [...]
Structured Policies for Efficient Knowledge-Guided Learning from Humans
Abstract: Imitation learning has achieved strong performance in sequential decision-making tasks, but typically requires large numbers of expert demonstrations, has limited generalization capability in unseen scenarios, and is challenging for laypeople without technical backgrounds. This thesis introduces structured policies, a framework that integrates human domain knowledge into imitation learning by using large language models (LLMs) to generate semantically meaningful policy structures from [...]
From Lab to Reality: Reliable 3D Vision in the Wild
VIRTUAL SEMINAR Abstract: While deep learning has revolutionized 3D computer vision, a significant gap remains between the performance achieved in controlled laboratory settings and that in complex, uncontrolled real-world environments. This talk addresses the critical challenges of robustness and generalization required to bridge this gap. In this presentation, I will first discuss our contributions to 3D [...]
Dynamic Route Guidance in Vehicle Networks by Simulating Future Traffic Patterns
Abstract: Roadway congestion leads to wasted time and money and environmental damage. One possible solution is adding more roadway capacity, but this can be impractical especially in urban environments and still may not make up for a poorly-calibrated traffic signal schedule. As such, it is becoming increasingly important to use existing road networks more efficiently. [...]