Site being updated, see my Research Lab page for current information.
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, computational sustainability, ecology, autonomous driving, physical chemistry and medical imaging.
Note for Potential Graudate Students
As of Sept 28, 2020 I have enough graduate students and I am not accepting new applications. Good luck with your search though.
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.
|Apr 16, 2021||
First news post, new website up and running...
more: First news post
- Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating TheoremIn 25th International Conference on Pattern Recognition (ICPR) 2021
- Isolation Mondrian Forest for Batch and Online Anomaly DetectionIn IEEE International Conference on Systems, Man, and Cybernetics (IEEE-SMC-2020) 2020
- A review of machine learning applications in wildfire science and managementEnvironmental Reviews 2020
- Distributed Nonlinear Model Predictive Control and Metric Learning for Heterogeneous Vehicle Platooning with Cut-in/Cut-out ManeuversIn Proceeding of the 59th IEEE Conference on Decision and Control (CDC-2020) 2020
- AI Education Through Real World ProblemsIn The Seventh Symposium on Educational Advances in Artificial Intellgience. 2017