Anthony Bonner

Anthony Bonner is an Associate Professor in the Department of Computer Science at the University of Toronto, where he has been a faculty member since 1991. He is also a member of the Collaborative Graduate Program in Genome Biology and Bioinformatics (CGPGBB). Previously, he served as a visiting professor at the University of Pennsylvania in 1999. His academic journey includes roles as an assistant professor at Indiana University, Bloomington, and a post-doctoral fellow at INRIA-Rocquencourt, France.

Dr. Bonner holds a B.Sc. in Mathematics and Physics from the University of Toronto, followed by M.S. and Ph.D. degrees in Computer Science from Rutgers University (1990 and 1991, respectively).

His research interests span machine learning, computer vision, bioinformatics, and genome mapping, with earlier work focusing on artificial intelligence, logical inference, database systems, and workflow management. His current research emphasizes generative AI for images and machine learning applications, as seen in courses like CSC2541 (Generative AI for Images) and CSC490 (Capstone Design in Machine Learning for Vision).

Dr. Bonner’s teaching includes advanced topics such as neural networks, kernel methods, and computational photography. He has contributed to curriculum development in machine learning, emphasizing practical applications and cutting-edge methodologies.