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David Radke, PhD

Sr Research Scientist Chicago Blackhawks dradke [at] blackhawks [dot] com

Links

Scholar  |   Resume  |   CV  |   LinkedIn  |   Twitter  

Experience

Education

August 2018 - June 2023

PhD - University of Waterloo   Image

Areas:
  • Artificial Intelligence
    • Multiagent Systems
    • Reinforcement Learning
  • Hockey Analytics
Advisors:

Dissertation:

  • The Impact of Teams in Multiagent Systems

    • 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.

    August 2015 - May 2018

    B.A. - Colorado College   Image

    Major:
    • Computer Science
    Minor:
    • Discrete Mathematics
    Advisor:

    Thesis: Using Artificial Neural Networks to Predict Wildfire Spread" - Top Undergraduate Research Project by the Council on Undergraduate Research.

    Work Experience

    June 2023 - Present

    Senior Research ScientistImage

    Chicago Blackhawks
    September 2022 - June 2023

    Advisor, Hockey Research & AnalyticsImage

    Chicago Blackhawks
    August 2018 - June 2023

    Research and Teaching Assistant   Image

    University of Waterloo
    September 2022 - December 2022

    Research Scientist Intern (Game AI)   Image

    Sony AI America
    June 2018 - August 2018

    Research Intern   Image

    Lawrence Livermore National Laboratory
    May 2017 - May 2018

    Undergraduate Research Assistant   Image

    UC Berkeley

    Community Experience

    Research Community Contributions

    2026

    Associate Editor

    Journal of Quantitative Analysis in Sports



    Program Committee Member

    AAMAS-26

    2025

    Associate Editor

    Journal of Quantitative Analysis in Sports



    Program Committee Member

    Linköping Hockey Analytics Conference (LINHAC-25)

    Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL-25) at RLC

    2024

    Associate Editor

    Journal of Quantitative Analysis in Sports



    Program Committee Member

    Linköping Hockey Analytics Conference (LINHAC-24)

    Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL-24) at RLC



    Panel Moderator

    Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL-24) at RLC

    2023

    Program Committee Member

    Linköping Hockey Analytics Conference (LINHAC-23)

    2022

    Program Committee Member

    AAAI-23

    Linköping Hockey Analytics Conference (LINHAC-22)

    Invited Talks

    2026

    2/5/26 - University of Waterloo

    2025

    10/30/25 - University of Wisconsin

    11/13/25 - Brock University

    2024

    2/19/24 - Dagstuhl Seminar

    4/26/24 - Simon Fraser University

    10/9/24 - Northwestern University

    10/24/24 - University of Waterloo (UWAGGS)

    12/13/24 - Multiagent Learning Seminar

    2023

    10/13/23 - Colorado College

    11/15/23 - University of Toronto (UTSPAN)

    12/1/23 - University of Alberta

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    Fun Facts

    Background

    • Hometown: Orinda, California
    • Citizenship: USA 🇺🇸 & Canada 🇨🇦
    • Language: English

    Athletics

    • Alumni - Assistant Captain - University of Waterloo varsity men's ice hockey (OUA; USports).
    • Alumni - Colorado College men's ice hockey (NCHC; NCAA Division 1).

    Featured Publication

    Presenting Multiagent Challenges in Team Sports Analytics
    [Click for Landing Page]

    David Radke and Alexi Orchard

    Autonomous Agents and Multiagent Systems (AAMAS) 2023, Blue Sky Track

    Publications

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    Adaptive Reward Sharing to Enhance Learning in the Context of Multiagent Teams
    [Click for Landing Page]

    Kyle Tilbury* and David Radke*

    RLC 2025
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    Simulating Tracking Data to Advance Sports Analytics Research
    [Click for Landing Page]

    David Radke* and Kyle Tilbury*

    AAMAS 2025 Demo
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    Dynamic Reward Sharing to Enhance Learning in the Context of Multiagent Teams
    [Click for Landing Page]

    Kyle Tilbury* and David Radke*

    AAMAS 2025 Extended Abstract
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    Towards a Better Understanding of Learning with Multiagent Teams
    [Click for Landing Page]

    David Radke, Kate Larson, Tim Brecht, and Kyle Tilbury

    IJCAI 2023
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    Analyzing Passing Metrics in Ice Hockey using Puck and Player Tracking Data
    [Click for Landing Page]

    David Radke, Jaxin Lu, Jackson Woloschuk, Tin Le, Daniel Radke, Charlie Liu, and Tim Brecht

    LINHAC 2023
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    Learning to Learn Group Alignment: A Self-Tuning Credo Framework with Multiagent Teams
    [Click for Landing Page]

    David Radke and Kyle Tilbury

    ALA at AAMAS 2023
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    Presenting Multiagent Challenges in Team Sports Analytics
    [Click for Landing Page]

    David Radke and Alexi Orchard

    AAMAS 2023 BlueSky
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    The Importance of Credo in Multiagent Learning
    [Click for Landing Page]

    David Radke, Kate Larson, and Tim Brecht

    AAMAS 2023
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    An Analysis of Engineering Students’ Responses to an AI Ethics Scenario
    [Click for Landing Page]

    Alexi Orchard and David Radke

    EAAI 2023
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    Best Paper Award

    Identifying Completed Pass Types and Improving Passing Lane Models
    [Click for Landing Page]

    David Radke, Tim Brecht, and Daniel Radke

    LINHAC 2022
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    Exploring the Benefits of Teams in Multiagent Learning
    [Click for Landing Page]

    David Radke, Kate Larson, and Tim Brecht

    IJCAI 2022
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    The Importance of Credo in Multiagent Learning
    [Click for Landing Page]

    David Radke, Kate Larson, and Tim Brecht

    Adaptive and Learning Agents Workshop (ALA) at AAMAS 2022
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    Passing and Pressure Metrics in Ice Hockey
    [Click for Landing Page]

    David Radke, Daniel Radke, Tim Brecht, and Alex Pawelczyk

    Artificial Intelligence for Sports Analytics (AISA), at IJCAI 2021
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    Beyond Measurement: Extracting Vegetation Height from High Resolution Imagery with Deep Learning
    [Click for Paper]

    David Radke, Daniel Radke, and John Radke

    RemoteSensing 2020
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    Can Future Wireless Networks Detect Fires?
    [Click for Paper]

    David Radke, Omid Abari, Tim Brecht, and Kate Larson

    BuildSys 2020
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    FireCast: Leveraging Deep Learning to Predict Wildfire Spread
    [Click for Paper]

    David Radke, Anna Hessler, and Dan Ellsworth

    IJCAI 2019
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    Assessing Extreme Weather - Related Vulnerability and Identifying Resilience Options for California's Interdependent Transportatiion Fuel Sector
    [Click for Paper]

    Refer to paper for author list.

    CEC 2018

    Media

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    Podcast: Hockey, AI, & the Future of Sports Analysis!

    2025
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    Game-changing insights using 5G technologies

    2023
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    Using data to better understand hockey performance

    2023
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    Thunderbirds graduate David Radke gets a job with the Chicago Blackhawks

    2022
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    Cheriton researchers develop new passing models with NHL tracking data, win best research paper award at LINHAC 2022

    2022
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    Cheriton Computer Science Students Reimagine the Hockey Fan Experience

    2020
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    Hacking Hockey

    2020
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    Designing IoT Devices to Benefit Society

    2019
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    3 Seniors to Present Wildfire Modeling Poster at Conference

    2018
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