As a member of the Striveworks customer engagements team, I apply the latest machine learning techniques to novel business problems across a variety of industries and sectors, including government. In addition to applying cutting edge computer vision and NLP algorithms (including LLMs), I am involved in the creation and maintenance of vital data infrastructure. Beyond my technical responsibilities, I also contribute to business strategy and internal process. Some highlights include:● Managed a team of 4 to build automated machine learning workflows to analyzetelemetry, social media, and overhead imagery using Python, Docker, and Flyte.This work was critical in closing a large deal with a key client.● Built and maintained key NLP and CV workflows in disconnected environments.● Led a team on a large tracking project involving PyTorch CV models. Applicationtracked anomalies through space and time on moving metal surfaces.● Architected and implemented a distributed DBSCAN application using a vectordatabase and deployed it in Kubernetes. Improved performance 100,000 times.● Built PyTorch speech synthesis models in non-austere, operational environments.

I was a graduate student in a theoretical physics lab working on understanding the dynamics and simulation of collisionless fluids. My work made predictions of dark matter signatures in the dynamics of Milky Way disk stars. In this capacity, I ran simulations with terabyte scale output and analyzed them. Some highlights include:● Implemented a novel simulation algorithm in an MPI-distributed C code to simulatea key process in galactic dynamics.● Discovered novel features in the vertical structure of stellar discs usingstatistical analysis in Python.● Studied dark matter substructure in the Milky Way using state-of-the-artphase-space clustering techniques.

I helped manage a distributed computing project, MilkyWay@Home, which uses asynchronous optimization/learning algorithms to fit properties dark matter in the Milky Way. My duties included development of simulation code, debugging issues with clients, and studying the performance of optimization algorithms.