Professor Hana Chockler's research interests lie in the area of causal reasoning and explainability. She is interested both in the theoretical concepts and in applications of these concepts to software engineering and machine learning systems (neural networks).

Her current large-scale applied research project is the explainability platform for black-box AI: Causal Responsibility-based Explanations (ReX). She is looking for students and postdoctoral researchers for a variety of projects related to ReX and extending ReX to other domains.

Historically, Hana's interest in causality arose from investigating the reasons and causes for the results of verification of hardware and software systems. She brought the concepts of causality from AI to formal verification and demonstrated their usefulness to the causal analysis and explanations of verification procedures.

In other directions, Professor Chockler has an ongoing research activity in the areas of formal verification, hardware synthesis, and learning for software analysis and exploration.

Her work is supported by the UKRI TAS Node in Governance and Regulation “Better Governance by Design”, UKRI TAS Hub, Royal Society International Exchanges Grant, and Google Faculty Award.

Research interests

• Explainable AI
• Actual causality
• Formal verification and synthesis

Public engagement

• Computerphile - Verifying AI 'Black Boxes'
• Computerphile - Defining Harm for Ai Systems

Further information

• Research Profile
• Research Funding
• Personal Website