PhD Thesis Defense

This thesis advances fine-grained reasoning under limited human supervision through several complementary approaches.

This dissertation addresses potential failure points in artificial agents.

This dissertation examines techniques for learning structure and discusses how the resulting background knowledge is used in decision making under uncertainty.

This dissertation studies algorithmic methods for constructing and optimizing threshold-logic circuits.

This dissertation explores how low-overhead dynamic analysis can be used to improve the reliability of Python software.

This dissertation develops a comprehensive framework for high-fidelity motion characterization, addressing challenges of sensitivity, robustness, and privacy.

This dissertation advances the design of practical privacy-preserving machine learning systems.

This thesis develops control frameworks for legged robots that bridge model-based trajectory optimization and data-driven learning

 This thesis examines three complementary roles of motion in computer vision.

This thesis develops and analyzes compact formulations for decision-making problems characterized by large action and large state sets.

This dissertation advances conversational AI by showing how multi-agent chatbots, thoughtful avatar design, and personalized interactions enhance engagement...

The central task developed in this work is to learn a global probabilistic model, often a graphical model, that is consistent with these observed marginals.