UNIVERSITY PARK, Pa. — Matthew Durbin, a nuclear engineering doctoral candidate, received a graduate scholarship from the Nuclear & Plasma Sciences Society (NPSS), a technical society within the Institute of Electrical and Electronics Engineers (IEEE).
The $1,500 award recognizes contributions to the fields of nuclear and plasma sciences, according to the NPSS website. Recipients are nominated for selection and up to four scholarships are awarded annually.
Durbin uses machine learning, an artificial intelligence technique wherein an algorithm learns and improves itself based on data, in his research to improve the efficiency of radioactive and nuclear material detection. His algorithms take in raw data gathered by various radiation detectors — which can range from drones to handheld or stationary monitors for imported cargo or public spaces — and work to separate the signals indicating the presence of radioactive material from unnecessary background data.
Durbin was specifically recognized for his work in improving directional detection. This method of detection attempts to indicate the direction of a radiation source. For example, a detection system could indicate a source 30 degrees to the left, with a margin of error of 10 degrees in either direction. With machine learning, Durbin is working to reduce or eliminate the discrepancy entirely so that potentially consequential radioactive materials can be located more efficiently.
“I was very surprised and honored to be selected, considering the number of potential nominees from around the world,” Durbin said. “I would also like to thank my adviser, Azaree Lintereur, for directing the work that was recognized.”
Lintereur, assistant professor of nuclear engineering, nominated Durbin for the recognition. Durbin, a student member of both the IEEE and NPSS, also received a Valentin Jordanov grant from the NPSS in 2019 to attend the annual conference.