The Distinguished Lecture Series Explores the Different Ways Machine Learning is Used in Research
The Distinguished Lecture series brings computer scientists to Columbia to discuss current issues and research that are affecting their particular fields.
This year, four experts covered topics on how machine learning is used in drug discovery, software testing, RNA splicing, and surrogate loss functions:
- Regina Barzilay, MIT
Modeling Chemistry for Drug Discovery: Current State and Unsolved Challenges - Koushik Sen, UC Berkeley
Automated Test Generation: A Journey from Symbolic Execution to Smart Fuzzing and Beyond - Oded Regev, Courant Institute, New York University
Using Machine Learning for Scientific Discovery in Biology - Shivani Agarwal, University of Pennsylvania
Surrogate Loss Functions in Machine Learning: What are the Fundamental Design Principles?
Below are a couple of the lectures from prominent faculty from universities across the country.
Automated Test Generation: A Journey from Symbolic Execution to Smart Fuzzing and Beyond
Koushik Sen, UC Berkeley
Surrogate Loss Functions in Machine Learning: What are the Fundamental Design Principles?
Shivani Agarwal, University of Pennsylvania
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