Space systems operations automation and AI technologies auditing systems architecting.

Research at the nexus of in-space operations & logistics, threat modelling, and large language models.

• Developed ML testing pipelines leveraging Databricks and MLFlow hosted on AWS, executing experiments with supervised time-series prediction with ensemble models in sklearn

• Refined and tested audio-spatial mapping algorithms utilizing unsupervised CNN models in Pytorch

• Engineered a robust data ingestion and preprocessing pipeline for audio HDF5 datasets to streamline experimental workflows and enhance training efficiency

Served on a sub-team building a computer vision framework that works in conjunction with a mounted camera system on an unmanned aerial vehicle that is capable of accurately identifying shapes and numbers from high altitudes. Used Python, OpenCV, SciKit, and Numpy to implement a key point locator utilizing Gaussian kernels. Additionally implemented a YOLO object tracking and detection framework using recurrent neural networks and scripted a rudimentary database with SQL in conjunction with ArcGIS to manage classification and geolocation data.

• Manages music library

• Runs rehearsals

• Leads parades