My research seeks dependable and transparent ways to augment human decision making in complex domains in the presence of spatial structure, large scale streaming data, or uncertainty. My focus is on developing new algorithms within the fields of Reinforcement Learning, Deep Learning and Ensemble Methods. I often work in collaboration with researchers in applied fields such as sustainable forest management, ecology, autonomous driving, physical chemistry and medical imaging.
In the field of Computational Sustainability, I have worked on learning predictive models of and optimizing policies for domains in invasive species control, forest harvest management and forest fire management. These types of domains offer unique challenges for traditional artificial intelligence and machine learning algorithms for decision making, prediction and anomaly detection.
Bio
Mark Crowley is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo and a member of the Waterloo Institute for Artifical Intelligence (waterloo.ai). He is also a core member of the Waterloo Institute for Complexity and Innovation (WICI). 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 on robust decision making under uncertainty in simulated Forest Fire domains.
Note for Potential Graduate Students
The global interest in AI/ML/RL is infectious and it is truly an exciting time to be in research in this field. However, interested students should be aware that I rarely accept new graduate students except ones that I know through courses I teach or other interactions at UWaterloo, at conferences, or through referrals from other colleagues. Unfortunately, if you email me with your interest in graduate school I probably will not be able to reply as I receive many such emails every day. Good luck in your search.
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.
