Nuclear Physics at TUNL
My first research position was at the Triangle Universities Nuclear Laboratory at Duke, on a DOE RENEW scholarship. I worked on the software side of nuclear spectroscopy, teaching computers to find the peaks that identify each nucleus.
What I built
I implemented machine learning peak-finding algorithms in Python and C++ on Linux, used for detector calibration of nuclear spectroscopy data. Calibration is unglamorous and essential. If the energy scale drifts, every measurement that follows is wrong.
What it taught me
Real detectors are noisy and real data is messy. An algorithm that works on a textbook spectrum will embarrass itself on a live one. TUNL taught me to validate against ground truth before trusting anything, and that habit has followed me into every project since.
