I’m a mathematical modeler, software developer, and experienced NBA front office executive who focuses on extracting insight from complex data. Currently, I develop statistical models and software tools that help NBA teams analyze game play and scout talent using high-resolution camera data. Before joining CTG, I worked in Research & Development for the Philadelphia 76ers. During my PhD, I collaborated with clinical epilepsy researchers to model and simulate human seizures. I’ve also built biophysical models of neural activity, studied biological networks using graph theory, and worked on image denoising.
Work Experience
Applied Scientist |Cleaning the Glass |
2025 - Present |
| CTG partners with NBA teams to receive 3D pose data from camera tracking systems and compute basketball-relevant events and estimates that help analyze the game in unprecedented detail. |
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Adjunct Professorial Lecturer |American University |
2017 - Present |
Instructor for Predictive Analytics ITEC 621 and Python Programming ITEC 596 / ITEC 600 |
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Manager, Research ↩ Data Scientist |Philadelphia 76ers |
2016 - 2025 |
| Working with the Research & Development team, I developed predictive models and web applications to help support coaches, scouts, executives, and sports scientists. |
Education
PhD, Computational Neuroscience |Boston University |
2016 |
Thesis work applied statistical point process theory to analyze spikes in the brain. These included both the familiar action potential from single cells and epileptic spikes, or "ictal discharges." Ictal discharges exhibit complex spatiotemporal structure, which we described and simulated using a point process generalized linear model (GLM). |
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MA, Mathematics |University of Georgia |
2011 |
Comprehensive exams in numerical analysis and complex variables. |
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BS, Mathematics / AB, English |University of Georgia |
2009 |
Relevant coursework includes multivariable calculus, real analysis, numerical analysis, ordinary differential equations, humanities computing. Research on algebraic graph theory and image denoising. |
Awards & Honors
Outstanding Teaching by an Adjunct |
2019 |
Kogod School of Business, American University |
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Finalist, ESPN Hackathon |
2016 |
Sloan Sports Analytics Conference |
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Predoctoral Training Grant, Epilepsy Foundation |
2015 |
"Data-driven modeling of seizure termination" |
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Travel Award |
2013 |
Department of Cognitive and Neural Systems, Boston University |
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Graduate Medical Sciences Scholarship |
2011 |
Graduate Program for Neuroscience, Boston University |
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Phi Beta Kappa |
2006 |
University of Georgia |
Computer Skills
Python |
JavaScript |
SQL |
Stan |
R |
Matlab |
Java |
Mathematica |
Maple |
Linux/Bash |
AWS |
LaTeX |
Interests and Activities
Point process models, generalized linear models |
Neural networks, deep learning |
Numerical analysis, high performance computing, quantum computing |
Sports analytics, basketball, ultimate frisbee |
Saxophone, piano |
