I am a fifth year PhD student at Harvard University, advised by Milind Tambe. I work on optimization and machine learning for social impact, with a focus on public health. My recent technical work integrates algorithms for discrete optimization into deep learning models, enabling end-to-end training of systems that combine prediction and decision making. I’ve also worked on optimization and active learning for interventions that use social networks to disseminate information. My aim is to enable better decisions under uncertainty, particularly in the context of interventions that improve health for vulnerable populations. Applications include a recent project on tuberculosis treatment in India, as well as a longer-running project on HIV prevention for homeless youth. Our algorithmically-driven HIV intervention was recently field-tested by Los Angeles-area homeless centers, with preliminary results showing large improvement compared to status quo techniques. I am supported by a National Science Foundation Graduate Research Fellowship. During summer 2019, I interned at Microsoft Research Redmond, where I was fortunate to be mentored by Eric Horvitz and Ece Kamar.

News

Preprints

  • Daniel B. Larremore, Bryan Wilder, Evan Lester, Soraya Shehata, James M. Burke, James A. Hay, Milind Tambe, Michael J. Mina, Roy Parker.
    Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance. [MedrXiv].
    June 27, 2020

  • Bryan Wilder, Marie Charpignon, Jackson A. Killian, Han-Ching Ou, Aditya Mate, Shahin Jabbari, Andrew Perrault, Angel Desai, Milind Tambe, Maimuna S. Majumder.
    Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City. [SSRN] [Code]
    May 29, 2020

Conference Publications

  • Bryan Wilder, Eric Horvitz, Ece Kamar.
    Learning to Complement Humans. [PDF].
    IJCAI-20. International Joint Conference on Artificial Intelligence. 2020.

  • Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe
    Influence maximization in unknown social networks: Learning policies for effective graph sampling. [arXiv].
    AAMAS-20. International Conference on Autonomous Agents and Multiagent Systems. 2020.
    Nominated for best paper at AAMAS 2020

  • Aaron Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe
    MIPaaL: Mixed Integer Program as a Layer. [arXiv].
    AAAI-20. AAAI Conference on Artificial Intelligence. 2020.

  • Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe
    Decision-Focused Learning of Adversary Behavior in Security Games. [arXiv].
    AAAI-20. AAAI Conference on Artificial Intelligence. 2020.

  • Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe.
    End to End Learning and Optimization on Graphs. [arXiv][code][slides].
    NeurIPS-19. Advances in Neural and Information Processing Systems. 2019.

  • Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe.
    Exploring Algorithmic Fairness in Robust Graph Covering Problems.
    NeurIPS-19. Advances in Neural and Information Processing Systems. 2019.

  • Po-Wei Wang, Priya L. Donti, Bryan Wilder, Zico Kolter.
    SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. [PDF].
    ICML-19. International Conference on Machine Learning. 2019.
    Honorable mention for best paper at ICML 2019

  • Alan Tsang*, Bryan Wilder*, Eric Rice, Milind Tambe, Yair Zick.
    Group-Fairness in Influence Maximization. [arXiv][code].
    IJCAI-19. International Joint Conference on Artificial Intelligence. 2019.
    *Equal contribution.

  • Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe.
    Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data. [arXiv].
    KDD-19. ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2019.

  • Matthew Staib*, Bryan Wilder*, Stefanie Jegelka.
    Distributionally Robust Submodular Maximization. [arXiv].
    AISTATS-19. International Conference on Artificial Intelligence and Statistics. 2019.
    *Equal contribution.

  • Bryan Wilder, Bistra Dilkina, Milind Tambe.
    Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. [PDF] [arXiv][code][datasets].
    AAAI-19. AAAI Conference on Artificial Intelligence. 2019.

  • Bryan Wilder, Yevgeniy Vorobeychik.
    Defending Elections Against Malicious Spread of Misinformation. [PDF] [arXiv][code].
    AAAI-19. AAAI Conference on Artificial Intelligence. 2019.

  • Mohammad Javad Azizi, Phebe Vayanos, Bryan Wilder, Eric Rice, Milind Tambe.
    Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources. [PDF]
    CPAIOR-18. International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research. 2018.
    Invited to Constraints journal fast track for outstanding papers

  • Bryan Wilder, Laura Onasch-Vera, Juliana Hudson, Jose Luna, Nicole Wilson, Robin Petering, Darlene Woo, Milind Tambe, Eric Rice.
    End-to-End Influence Maximization in the Field. [PDF]
    AAMAS-18. International Conference on Autonomous Agents and Multiagent Systems. 2018.
    Nominated for best student paper

  • Bryan Wilder, Han Ching Ou, Kayla de la Haye, Milind Tambe.
    Optimizing network structure for preventative health. [PDF]
    AAMAS-18. International Conference on Autonomous Agents and Multiagent Systems. 2018.

  • Bryan Wilder, Yevgeniy Vorobeychik.
    Controlling Elections through Social Influence. [arXiv] [PDF] [Supplement]
    AAMAS-18. International Conference on Autonomous Agents and Multiagent Systems. 2018.

  • Lily Hu, Bryan Wilder, Amulya Yadav, Eric Rice, and Milind Tambe.
    Activating the “Breakfast Club”: Modeling Influence Spread in Natural-World Social Networks. [arXiv]
    AAMAS-18. International Conference on Autonomous Agents and Multiagent Systems. 2018.

  • Bryan Wilder, Sze-Chuan Suen, Milind Tambe.
    Preventing infectious disease in dynamic populations under uncertainty. [PDF] [Supplement]
    AAAI-18. AAAI Conference on Artificial Intelligence. 2018.

  • Bryan Wilder.
    Equilibrium computation and robust optimization in zero sum games with submodular structure. [arXiv] [Code]
    AAAI-18. AAAI Conference on Artificial Intelligence. 2018.

  • Bryan Wilder.
    Risk-sensitive submodular optimization. [PDF] [Supplement] [Code]
    AAAI-18. AAAI Conference on Artificial Intelligence. 2018.

  • Bryan Wilder, Nicole Immorlica, Eric Rice, Milind Tambe.
    Maximizing influence in an unknown social network. [PDF] [Supplement]
    AAAI-18. AAAI Conference on Artificial Intelligence. 2018.

  • Amulya Yadav, Bryan Wilder, Robin Petering, Eric Rice, Milind Tambe.
    Influence Maximization in the Field: The Arduous Journey from Emerging to Deployed Application. [PDF]
    AAMAS-17. International Conference on Autonomous Agents and Multiagent Systems. 2017.
    Nominated for Best Paper (7 out of 288 papers)

  • Bryan Wilder, Amulya Yadav, Nicole Immorlica, Eric Rice, Milind Tambe.
    Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network. [PDF] [Supplement]
    AAMAS-17. International Conference on Autonomous Agents and Multiagent Systems. 2017.

  • Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole Sintov, Milind Tambe.
    Divide to Defend: Collusive Security Games.
    GameSec-16. Conference on Decision and Game Theory for Security. 2016.

  • Bryan Wilder and Gita Sukthankar.
    Sparsification of Social Networks Using Random Walks. [PDF] [Code]
    SocialCom-15. International Conference on Social Computation. 2015.

Journal Publications

  • Eric Rice, Robin Petering, Amanda Yoshioka-Maxwell, Jaih Craddock, Darlene Woo, Nicole Wilson, Laura Onasch-Vera, Bryan Wilder Amulya Yadav, Milind Tambe.
    Piloting the Use of Artificial Intelligence to Enhance HIV Prevention Interventions for Youth Experiencing Homelessness. [Link]
    Journal of the Society for Social Work and Research. 2018.

  • Anne Kandler, Bryan Wilder, Laura Fortunato.
    Inferring individual-level processes from population-level patterns in cultural evolution. [Full text] [Code]
    Royal Society Open Science. 2017.

  • Bryan Wilder and Anne Kandler.
    Inference of Cultural Transmission Modes Based on Incomplete Information. [PDF]
    Human Biology. 2015.

  • Bryan Wilder and Kenneth O. Stanley.
    Reconciling Explanations for the Evolution of Evolvability. [PDF]
    Adaptive Behavior. 2015.

  • Bryan Wilder and Kenneth O. Stanley.
    Altruists Proliferate Even When at a Selective Disadvantage Within their Own Niche. [Full text]
    PLOS One. 2015.