About
Anthony J. Bonner is an Associate Professor in the Department of Computer Science at the University of Toronto. He 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. He has been a faculty member at the University of Toronto since 1991, previously serving as an assistant professor at Indiana University and a post-doctoral fellow at INRIA-Rocquencourt. He is affiliated with the Collaborative Graduate Program in Genome Biology and Bioinformatics (CGPGBB).
His research focuses on machine learning, data mining, bioinformatics, computational biology, and numerical methods. Earlier work includes contributions to genome mapping, artificial intelligence, logical inference, database systems, and workflow management. He has taught numerous courses, including Machine Learning, Numerical Methods, and specialized topics like Generative AI for Images and Convex Optimization.
He has held visiting positions, including at the University of Pennsylvania in 1999. His teaching spans undergraduate and graduate levels, with courses emphasizing practical applications in scientific computing and machine learning. His work bridges theoretical foundations and real-world problems in fields like healthcare, robotics, and computational finance.
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