AI and Machine learning for Trustworthy Autonomous Intelligent Machines and Systems

Oishi Deb (Ph.D. Student)

This project focuses on theoretical as well as applied research on trustworthy autonomous intelligent machines and systems to ensure better decision-making in safety-critical applications. It will address vulnerabilities and countermeasures of ML and AI algorithms that are being used in Autonomous Systems (AS). Uncertainty handling and error propagation will be considered as well as various scenarios/methods will also be under investigation. AIMS CDT Advisor: Michael A. Osborne and Primary/Industry Advisors: Philip Torr and Christian Rupprecht.

Primary Advisor:	Michael A. Osborne (University of Oxford)
Industry Advisor:	Philip H. S. Torr (University of Oxford)
PhD Duration:	01 October 2023 - 31 July 2027