Assistant Professor, Electrical and Computer Engineering
Core Member, Waterloo Institute for Complexity and Innovation

My research spans multiple areas of Artificial Intelligence and Machine Learning foocusses on algorithms, tools and theory at the intersection of Machine Learning, Optimization and Probabilistic Modelling. In particular I look into the challenges for traditional machine learning and optimization algorithms that arise in domains with spatial dynamics and large streaming datasets. I often work in collaboration with researchers in other fields such as sustainable forest management, ecology, automotive design and medical imaging.

Bio

Mark Crowley is an Assistant Professor in the Pattern Recognition and Machine Intelligence group in the Department of Electrical and Computer Engineering at the University of Waterloo. He is a core member of the Waterloo Institute for Complexity and Innovation. He received his Ph.D. and M.Sc. in Computer Science from the University of British Columbia working in the Laboratory for Computational Intelligence with David Poole. Before coming to Waterloo he did a postdoc at Oregon State University working with Tom Dietterich’s machine learning group on robust decision making under uncertainty in simulated Forest Fire domains.

Writing

Besides my publications, you can follow my Computationally Thinking blog or @compthink on twitter for links and thoughts on Artificial Intellgience, Machine Learning and how technology and science are advancing.