Summary
Eric Pooser is a Senior Research Scientist with 11 years of hands-on experience translating experimental nuclear physics and high-throughput instrumentation into production-ready data acquisition and machine learning pipelines. At Georgia Tech Research Institute he led development of the SAW-ML pipeline that fuses spectroscopy, mass spec, and elemental analysis via advanced feature engineering and modern ML to solve forensic and provenance problems for DoD programs. His background includes building 45 Gb/s streaming DAQ systems, custom C libraries for 100Gb networks, and real-time monitoring frameworks—skills that bridge low-level systems engineering and applied data science. A PhD in nuclear physics and prior roles at Jefferson Lab show deep expertise in detector design, Monte Carlo simulation, and online diagnostics. Colleagues would note his uncommon combination of experimental rigor and production-focused software craftsmanship, enabling rapid transition from lab prototype to operational analytics. Based in Newport News, VA, he pairs domain knowledge in physical measurements with practical ML deployments to classify complex chemical and biological signatures.
11 years of coding experience
2 years of employment as a software developer
High School Diploma, Cum Laude, High School Diploma, Cum Laude at Riverside Military Academy
Doctor of Philosophy - PhD, Nuclear Physics, Magna Cum Laude, Doctor of Philosophy - PhD, Nuclear Physics, Magna Cum Laude at Florida International University
Bachelor of Science - BS, Physics, Cum Laude, Bachelor of Science - BS, Physics, Cum Laude at University of North Georgia
English