Assistant Professor, Machine Learning Department
Carnegie Mellon University
- Underspecified and unclear: have you appropriately defined your model and the properties it satisfies?
- Understanding causal structure: validating the decisions your machine made
-How can you explain why a model did something? Why did the ML choose a certain course of action?
- Resilience and robustness: The importance of factoring in domain adaptation and distribution shift
- Anomaly detection: quantifying and actively compensating by modifying your beliefs and constraints