معرفی
Dr. Michael Horsch is a retired Associate Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on Artificial Intelligence, Reasoning Under Uncertainty, Constraint Satisfaction, and Machine Learning. He has contributed to bioinformatics through the P2IRC sub-theme, linking genotype and environment to phenotype using computational methods.
Education: PhD (Computer Science, UBC, 1998), M.Sc. (Computer Science, UBC, 1990), B.Sc. (Computer Science & Physics, University of Toronto, 1988). Postdoctoral work at Simon Fraser University (2000).
Research interests emphasize practical AI applications, including Bayesian networks, constraint satisfaction algorithms, and machine learning. His work bridges theoretical foundations and real-world problems, such as path planning and sensor optimization.
Teaching highlights include courses on AI (CMPT 317), programming (CMPT 145), and machine learning (CMPT 423/820). He revised first-year curricula to improve student accessibility, replacing C++ with more user-friendly languages. Recognized for teaching excellence with the 2014 Provost’s Award.
Publications span constraint satisfaction, probabilistic reasoning, and Bayesian networks, with notable contributions to algorithm design and optimization.
