Tom Magelinski

Tom Magelinski is currently a Senior Data Scientist at The Johns Hopkins University Applied Physics Laboratory, specializing in information extraction and generative AI since July 2023. In this role, Tom develops applications to assist analysts in processing large data streams, focusing on projects such as a validation framework for a retrieval augmented generation pipeline and a synthetic data generation tool using large language models. Prior to this position, Tom was a PhD candidate at Carnegie Mellon University's School of Computer Science from August 2017 to May 2023, under the guidance of Professor Kathleen Carley. Additional experience includes internships at Spotify and Thermo Systems, as well as research roles at Ross Dynamics Laboratory, Math Observatory, and the Bio-Inspired Fluids Laboratory. Tom holds a PhD in Computer Science with a focus on Societal Computing from Carnegie Mellon University and a Bachelor's degree in Engineering Science and Mechanics from Virginia Tech.