Thumb ticker md amir hossein karimi  phd student

Causality of Enhanced Model Interpretability

Amir-Hossein Karimi (Ph.D. Student)

As machine learning is increasingly used to inform decision-making in consequential real-world settings (e.g., pre-trial bail, loan approval, or prescribing life-altering medication), it becomes important to explain how the system arrived at its decision, and also suggest actions to achieve a favorable decision. My thesis objective is to study, design, and deploy methods to address the second question, specifically on generating counterfactual explanations ( and minimal interventions ( Thus my focus is on the intersection of machine learning interpretability, causal and probabilistic modelling, and social philosophy and psychology.

Primary Host: Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)
Exchange Host: Thomas Hofmann (ETH Zürich)
PhD Duration: 01 October 2018 - Ongoing
Exchange Duration: - Ongoing