Michael Boratko

Interests

Michael's current research centers around box lattice models and structured prediction. He is broadly interested in program synthesis, deep learning, optimization techniques, and interpretability. He enjoys exploring the theoretical underpinnings of machine learning and identifying areas where my mathematical background can be leveraged to increase understanding or improve performance. He is also interested in game theory, parallel and distributed algorithms, programming languages and theory of computation.