Phillip M. Kim

Professor, University of Toronto

Philip M. Kim is a professor at the University of Toronto at the Donnelly Centre and the Departments of Computer Science and Molecular Genetics. In his academic research, he has been developing novel machine learning methods for protein and peptide engineering and authored over 90 publications, 7 invention disclosures and 5 patent applications. He has co-founded several biotechnology companies and serves as consultant and member of the scientific advisory board for others. Before setting up his lab in 2009, he was a postdoctoral fellow at Yale University and an associate with McKinsey & Co. He holds a Ph.D. from the Artificial Intelligence Laboratory and Department of Chemistry at the Massachusetts Institute of Technology and a B.S. in Physics and Biochemistry from the University of Tuebingen.

Machine Learning Methods for De Novo Antibody Design

In this webinar, our expert speaker Dr. Phillip Kim from the University of Toronto will be discussing the ML methods he currently implements in his lab that enables de novo antibody design. He will also cover ML-based sequence design and scoring methods, as well as diffusion models.

Webinar