Curriculum vitae
Maximilian (Max) J. Gebauer
Philadelphia · gebauerm@sas.upenn.edu
Updated August 5, 2026
Education
University of Pennsylvania
Ph.D. Candidate, Philosophy
Areas of specialization: Philosophy of Science; Bayesianism. Areas of competence: Political Philosophy; Environmental Philosophy.
The Wharton School, University of Pennsylvania
M.A., Statistics & Data Science
Thesis: “Sparse Control Selection For Spatial Epidemiological Data: Double Lasso And County COVID-19 Mortality.”
Washington and Lee University
B.A., Philosophy & Poverty and Human Capability Studies, magna cum laude; Honors in Philosophy
University of Oxford, Mansfield College
Visiting Student Programme
Forthcoming publication
“Bayesian Practice and the Persistence of Inductive Risk”
Philosophy of Science, forthcoming.
Working papers
“Opponent-Adjusted Evaluation of NFL Pass Blocking and Pass Rushing Performance”
Jonathan Pipping-Gamón, Maximilian J. Gebauer, Victoria Lee, Kenny Watts, and Abraham J. Wyner.
Interpretable ridge-regularized Bradley-Terry models for player-level pass-blocking and pass-rushing evaluation using opponent-dependent tracking interactions.
FAIR xwOBA
Maximilian J. Gebauer.
A player-trait-free model of expected weighted on-base average in Major League Baseball that outperformed the declared Statcast comparators across six rolling held-out development seasons and supports new analysis of the game value associated with Sprint Speed.
Aug. 2026
Research & professional experience
Technical Lead, Wharton Analytics Fellows
Summer Lab Associate
Wharton Sports Analytics and Business Initiative
Graduate Mentor, Perry World House
Mentored an undergraduate research team on quantitative approaches in climate governance.
Intern, Center for Ethics and the Rule of Law
Coauthored white papers combining quantitative and qualitative analysis of proposed FISA Section 702 reforms.
Intern, U.S. Federal District Court
Produced analytical research for legal–academic partnerships.
Teaching experience
Instructor and Teaching Assistant, University of Pennsylvania
Instructor of record for Philosophy of Science and Introductory Statistics. Teaching-assistant portfolio: Philosophy of Science, Introduction to Logic, Bioethics, Saving the Planet: Tools for the Climate Emergency, Modern Data Mining, Applied Bayesian Modeling, Applied Regression Analysis for Health Policy Research, and Introduction to Statistics for Health Policy.
Teaching Fellow, Wharton Data Science Academy
Taught high school students in an intensive summer program; delivered lectures on neural networks and ensemble methods, advised student projects, and supported assignments.
Teaching Assistant, Wharton Moneyball Academy
Advised high school student projects in sports statistics and provided coding and analytical support in the Philadelphia and San Francisco programs.
Talks, Presentations, and Invited Lectures
“Approximating Posterior Distributions with Variational Bayes”
Applied Bayesian Modeling
“A Dynamic Rating Scheme for NFL Pass Rushers”
New England Symposium for Statistics in Sports; Wharton Sport Analytics and Business Summit
“Judgment and Decision-making under Uncertainty”
Repairing the Planet: Tools for the Climate Emergency
“Expected Utility Maximization and Environmental Decision-making”
Repairing the Planet: Tools for the Climate Emergency
Academic leadership
- Chair, “AI as Method” symposium, 29th Biennial Meeting of the Philosophy of Science Association, 2024.
- Chair, “Applied Ethics” colloquium, 119th Annual Meeting of the Eastern Division of the American Philosophical Association, 2023.
- Co-developed a new introductory logic course at the University of Pennsylvania, 2024.
Selected coursework & research
Statistics & Data Science
Applied Regression; Bayesian Modeling; Data Mining; Observational Studies; Probability; Statistical Computing; Forecasting & Time Series; Non-parametric Methods.
Philosophy
Philosophy of Science; Mathematical Logic; Logic; Political Philosophy; Metaethics; Contemporary Ethical Theory; Proseminar; Kant and the a priori; Modern Political Philosophy; Epistemology and Perception.
Sparse Control Selection For Spatial Epidemiological Data
Applied post-double-selection LASSO with a negative-binomial regression model and Markov random field spatial controls to investigate the association between U.S. county-level partisanship and COVID-19 mortality.
Awards & fellowships
- Perry World House Graduate Fellow, 2025–26.
- Fishman Fellowship, University of Pennsylvania, 2022–present.
- Benjamin Franklin Fellowship, University of Pennsylvania, 2022–present.
- Fontaine Graduate Fellowship, University of Pennsylvania, 2022–present.
- Dissertation Research Award, University of Pennsylvania, 2025.
- Edward Dodd Award; Charles Thomas Boggs Prize; The Young Scholarship; William Wells Chaffin Memorial Scholarship, Washington and Lee University, 2022.
- The Grenader Family Prize, Mansfield College, University of Oxford, 2020.
Methods & software
Proficient in R, Stan, and LaTeX; familiar with Python, Excel, and Stata. Methods include regression analysis, Bayesian modeling, nonparametric methods, stochastic simulation, and machine learning. Software includes RStudio, VS Code, Jupyter, GitHub, and Overleaf.