
Dissertation:
Artificial Intelligence (AI): My PhD research studyied how teams impact the behavior that AI agents learn. This includes studying group dynamics, emergent behavior, and game theoretical incentives in challenging environments.
Hockey Analytics: During graduate school, I used tracking data from the National Hockey League (NHL) to develop analytics for AI systems with the goal to quantify performance in new ways, such as passing performance and player positioning.

Thesis: Using Artificial Neural Networks to Predict Wildfire Spread" - Top Undergraduate Research Project by the Council on Undergraduate Research.
Journal of Quantitative Analysis in Sports
Linköping Hockey Analytics Conference (LINHAC-25)
Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL-25) at RLC
Journal of Quantitative Analysis in Sports
Linköping Hockey Analytics Conference (LINHAC-24)
Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL-24) at RLC
Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL-24) at RLC


Front office advisor of analytics.
Chicago Blackhawks
I spearhead several research projects on cutting-edge AI research. I also organize and grade for undergraduate computer science courses.
University of Waterloo
Research Scientist Intern with the Game AI team.
Sony AI America
Summer research intern in the Computation department.
Lawrence Livermore National Laboratory
I worked in a research team assessing the risk of wildland fire and coastal flooding on California's Transportation Fuel Sector.
UC Berkeley
Kyle Tilbury* and David Radke*
RLC 2025David Radke* and Kyle Tilbury*
AAMAS 2025 Demo
David Radke, Kate Larson, Tim Brecht, and Kyle Tilbury
IJCAI 2023
David Radke, Jaxin Lu, Jackson Woloschuk, Tin Le, Daniel Radke, Charlie Liu, and Tim Brecht
LINHAC 2023
David Radke and Alexi Orchard
AAMAS 2023 BlueSky
David Radke, Kate Larson, and Tim Brecht
AAMAS 2023
Alexi Orchard and David Radke
EAAI 2023
David Radke, Tim Brecht, and Daniel Radke
LINHAC 2022
David Radke, Kate Larson, and Tim Brecht
IJCAI 2022
David Radke, Kate Larson, and Tim Brecht
Adaptive and Learning Agents Workshop (ALA) at AAMAS 2022
David Radke, Daniel Radke, Tim Brecht, and Alex Pawelczyk
Artificial Intelligence for Sports Analytics (AISA), at IJCAI 2021
David Radke, Daniel Radke, and John Radke
RemoteSensing 2020
David Radke, Omid Abari, Tim Brecht, and Kate Larson
BuildSys 2020
David Radke, Anna Hessler, and Dan Ellsworth
IJCAI 2019
Refer to paper for author list.
CEC 2018