PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Trustworthy Learning using Uncertain Interpretation of Data

GHC 6501

Abstract: Motivated by the potential of Artificial Intelligence (AI) in high-cost and safety-critical applications, and recently also by the increasing presence of AI in our everyday lives, Trustworthy AI has grown in prominence as a broad area of research encompassing topics such as interpretability, robustness, verifiable safety, fairness, privacy, accountability, and more. This has created [...]