PDF


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.

Adjunct Professorial Lecturer |

American University

2017 - Present

Instructor for Predictive Analytics ITEC 621 and Python Programming ITEC 596 / ITEC 600

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).

MA, Mathematics |

University of Georgia

2011

Comprehensive exams in numerical analysis and complex variables.
Relevant coursework includes numerical analysis, dynamical systems, partial differential equations, quantum mechanics, and quantum computing.

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

Finalist, ESPN Hackathon

2016

Sloan Sports Analytics Conference

Predoctoral Training Grant, Epilepsy Foundation

2015

"Data-driven modeling of seizure termination"

Travel Award

2013

Department of Cognitive and Neural Systems, Boston University

Graduate Medical Sciences Scholarship

2011

Graduate Program for Neuroscience, Boston University

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