Aditi Krishnapriyan (UC Berkeley): Schmidt AI in Science Speaker Series

Organized by the University of Chicago’s Eric and Wendy Schmidt AI in Science Fellowship Program.

Agenda
4:00pm – 4:45pm:  Presentation
4:45pm – 5:00pm:  Q&A
5:00pm – 5:30pm: Reception

Meeting location
William Eckhardt Research Center. Room 401
5640 S Ellis Avenue, Chicago, IL 60637
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Bio: Aditi Krishnapriyan, Assistant Professor, University of California, Berkeley. I  am interested in developing methods in machine learning that are driven by the distinct challenges and opportunities in the natural sciences, with particular interest in physics-inspired machine learning methods. Some areas of exploration include general learning strategies exploring the relevance of physical inductive biases and ML models for scientific problems, the advantages that ML can bring to classical physics-based numerical solvers (such as through end-to-end differentiable frameworks and implicit layers), and better learning strategies for distribution shifts in the physical sciences. These methods are informed by and grounded in applications in atomistic and continuum problems, including fluid mechanics, molecular dynamics, and other related areas. This work also includes interfacing with other fields including numerical analysis, dynamical systems theory, quantum mechanics, computational geometry, optimization, and category theory.