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General Information

Full Name William H. W. Thompson
Email wthomps3@uvm.edu
Website https://www.willhwthompson.com
GitHub https://github.com/WillHWThompson

Education

  • 2022 – Present
    Ph.D. in Complex Systems & Data Science
    University of Vermont
  • 2016 – 2020
    B.A. in Liberal Arts
    St. John’s College, Santa Fe

Experience

  • Aug 2022 – Present
    Graduate Research Assistant
    University of Vermont
    • Developed a Fourier-space representation for Bayesian Neural Networks (BNNs) to enable exact, sampling-free inference and learning, bypassing computational bottlenecks of MCMC.
    • Designed non-parametric Bayesian models for contagion processes, enabling the simultaneous joint reconstruction of network topology and spreading dynamics from time-series data.
    • Engineered a Graph Machine Learning (GML) pipeline to infer latent interaction kernels governing stochastic network dynamics.
  • Jun 2025 – Oct 2025
    Graduate Research Intern
    Los Alamos National Laboratory
    • Developed BPTuning, a high-performance Julia framework for graphical model inference on loopy graphs.
    • Derived a proof of optimality for a method that optimizes effective parameters to cancel out Belief Propagation (BP) approximation errors on cyclic topologies.
    • Implemented a reconstruction-based objective function to serve as a tractable proxy for exact likelihood maximization.
  • Apr 2023 – Jan 2025
    Lead Data Scientist
    Zoodiker
    • Engineered an end-to-end NLP pipeline to process screenplay text, utilizing sentiment analysis and structural extraction algorithms to quantify narrative arcs.
    • Designed anomaly detection heuristics to correlate specific character dynamics with reader engagement deviations.
    • Implemented a full-stack analytics dashboard (SQL/React/Python) to visualize high-dimensional text features.
    • Patent Pending: Filed for novel techniques in automated narrative structural analysis.
  • Jan 2021 – Aug 2022
    Post-Baccalaureate Researcher
    Los Alamos National Laboratory
    • Developed a 200+ unit photon detection system for the Coherent Captain Mills (CCM) particle physics experiment.
    • Enhanced the data acquisition system (DAQ), doubling capacity and improving stability for 10-ton scale data capture.
    • Led the development of detector control software, integrating sensor arrays and automated emergency alerts.
  • Aug 2020 – Dec 2020
    Data Scientist
    MITRE Corporation
    • Applied complex systems science to analyze satellite network structures and mitigate failure cascades.
    • Co-developed Strategy Mining, an open-source genetic programming tool for evolving Agent-Based Models (ABMs).
    • Conducted semantic analysis of judicial documents to improve legal search accuracy.
  • Jun 2018 – Aug 2018
    Undergraduate Research Fellow
    Carnegie Mellon University
    • Executed a research project on the structural analysis of philosophical texts using NLP and Random Walk algorithms; findings published as first author.
  • Jun 2017 – Jun 2018
    Undergraduate Researcher
    Santa Fe Institute
    • Conducted independent research using NLP and machine learning to explore the narrative function of the chorus in Greek tragedies.

Grants & Awards

  • Second Place, University of Vermont Computing Student Research Day (2023) — Presented research on developing learnable asynchronous models of opinion dynamics.
  • Third Place, University of Vermont Computing Science Research Day (2022) — Awarded for research employing evolutionary algorithms to develop robust facility placements.
  • MITRE Best Paper Incentive Prize (2022) — Paper 'The Structure and Dynamics of US Common Law' recognized as best out of hundreds published that year.
  • Large Team Distinguished Performance Award, LANL (2022) — Recognized for construction and dark matter search leadership with Coherent Captain Mills Detector.
  • Science Undergraduate Laboratory Internship (SULI) Grant, DOE (2020) — Selective DOE grant for post-baccalaureate research at LANL.
  • Dean's Award for College Service, St. John's College (2020) — Recognized for exceptional leadership and dedication.
  • Robert Neidorf Memorial Scholarship (2018)
  • ARIEL Grant — St. John's College (2017)

Publications (Preprints)

  • M. C. Boudreau, W. H. W. Thompson, C. M. Danforth, J.-G. Young, L. Hébert-Dufresne. "[Sensitivity analysis of epidemic forecasting and spreading on networks with probability generating functions](https://arxiv.org/abs/2506.24103)." arXiv:2506.24103 (2025).
  • W. H. W. Thompson, Z. Wojtowicz, S. DeDeo. "[Levy Flights of the Collective Imagination](https://arxiv.org/abs/1812.04013)." arXiv:1812.04013 (2018).

Publications (Peer-Reviewed Journals)

  • A. A. Aguilar-Arevalo *et al.* "First Event-by-Event Identification of Cherenkov Radiation from Sub-Mev Particles in Liquid Argon." *Phys. Rev. Lett.* **135** (17) 171804 (2025).
  • A. A. Aguilar-Arevalo *et al.* "Measurement of the liquid argon scintillation pulse shape using differentiable simulation in the coherent CAPTAIN-Mills experiment." *Phys. Rev. D* **112** (7) 072010 (2025).
  • N. W. Landry, W. H. W. Thompson, L. Hébert-Dufresne, J.-G. Young. "[Reconstructing networks from simple and complex contagions](https://doi.org/10.1103/PhysRevE.110.L042301)." *Phys. Rev. E* **110** (4) L042301 (2024).
  • A. A. Aguilar-Arevalo *et al.* "[Testing meson portal dark sector solutions to the MiniBooNE anomaly at the Coherent CAPTAIN-Mills experiment](https://doi.org/10.1103/PhysRevD.109.095017)." *Phys. Rev. D* **109** (9) 095017 (2024).
  • A. A. Aguilar-Arevalo *et al.* "[Axion-Like Particles at Coherent CAPTAIN-Mills](https://doi.org/10.1103/PhysRevD.107.095036)." *Phys. Rev. D* **107** 095036 (2023).
  • A. A. Aguilar-Arevalo *et al.* "[First Leptophobic Dark Matter Search from Coherent CAPTAIN-Mills](https://doi.org/10.1103/PhysRevLett.129.021801)." *Phys. Rev. Lett.* **129** 021801 (2022).
  • A. A. Aguilar-Arevalo *et al.* "[First dark matter search results from Coherent CAPTAIN-Mills](https://doi.org/10.1103/PhysRevD.106.012001)." *Phys. Rev. D* **106** 012001 (2022).
  • M. Koehler *et al.* "The structure and dynamics of US common law." *Front. Phys.* (Jan 2022).

Conference Proceedings

  • W. Thompson *et al.* "[Evolving Robust Facility Placements](https://doi.org/10.1145/3583133.3590712)." *Companion Proc. GECCO 2023*, pp. 775-778.
  • A. Isherwood, W. Thompson, *et al.* "[Modeling Macaque Fighting Dynamics with the Evolutionary Model Discovery Framework](https://doi.org/10.1007/978-3-031-37553-8_9)." *CSS Society Conference 2022*.

Teaching & Mentorship

  • 2023 – Present
    Graduate Research Mentor
    University of Vermont
    • Directed a research cohort of 5 undergraduate interns over two semesters; managed the development of a Machine Learning pipeline to detect student-authored news content across hundreds of U.S. publications.
    • Mentored summer interns on individual projects in network science and complex systems.
    • Guest Lecturer: Delivered lectures on 'Introduction to Network Science,' 'Stochastic Cellular Automata,' and 'Chaos & Fractals' for graduate and undergraduate courses.
  • Summers 2021, 2022
    Post-Baccalaureate Mentor
    Los Alamos National Laboratory
    • Supervised undergraduate interns during two consecutive summer sessions, providing technical guidance on C++ development and detector hardware calibration.
    • Facilitated onboarding for new researchers, training them on laboratory safety protocols and data acquisition software.
  • May 2019 – May 2021
    Head Senior Lab Assistant
    St. John's College
    • Directed the setup and instructional design of a tabletop quantum optics lab and trained junior assistants in experimental protocols.

Selected Talks

  • Invited Seminars
    • The Emergence of Inequality with Two Models of Social Dynamics — Dartmouth College Applied Math Seminar Series, Hanover, NH (Oct 2023)
    • Understanding Polarization with the Non-Linear Voter Model on Higher Order Networks — Vermont-KIAS Workshop on Higher Order Interactions, Burlington, VT (Sept 2023)
    • Searching for Light Dark Matter with Coherent Captain Mills — University of New Mexico NUPAC Colloquia Series, Albuquerque, NM (May 2021)
  • Conference Presentations
    • Sensitivity of epidemic forecasts with statistical condition estimation — Dynamics Days 2025, Denver, CO (Poster)
    • Inferring Interaction Kernels In Stochastic Opinion Dynamics Models — NetSci 2024, Québec City (Jun 2024)
    • Understanding Polarization In the Higher Order Non-Linear Voter Model — Dynamics Days 2024, Davis, CA (Jan 2024)
    • The Emergence of Polarization in the Non-Linear Voter Model on Higher Order Networks — Joint Mathematics Meeting 2024, San Francisco, CA (Jan 2024)
    • Evolving Robust Facility Placements — GECCO 2023, Lisbon, Portugal (Jul 2023)

Service & Outreach

  • Peer Reviewer: Physical Review E (2024), NPJ Complexity (2024)
  • Public Outreach: Delivered talks on 'The Mathematics of Making Coffee' and Percolation theory at Vermont State University (2024), Vermont Science Olympiad (2024), and UVM MATHCOUNTS (2024)

Technical Skills

  • Languages: Julia, Python, C++, SQL, Bash, LaTeX
  • Machine Learning & Data: PyTorch, Flux.jl, NetworkX, SciPy, Pandas, Scikit-learn
  • Methods: Bayesian Inference, Graph Neural Networks, MCMC, Agent-Based Modeling, NLP
  • Tools: Git, Docker, UNIX/Linux, High-Performance Computing (HPC)

References

Peter Dodds Professor, Complex Systems Center, University of Vermont — pdodds@uvm.edu
Richard Van De Water Staff Scientist, P-2 Pure and Applied Physics, Los Alamos National Labs — vdwater@lanl.gov
Simon DeDeo Assistant Professor, Carnegie Mellon University — sdedeo@andrew.cmu.edu
Matthew Koehler Applied Complexity Scientist, MITRE Corporation — mkoehler@mitre.org