Poster
in
Affinity Workshop: Women in Machine Learning

Detecting Synthetic Opioids with NQR Spectroscopy and Complex-Valued Signal Denoising

Amber Day · Natalie Klein · Michael Malone · Harris Mason · Sinead Williamson


Abstract:

Dangerous synthetic opioids (e.g., fentanyl) are currently synthesized abroad and shipped into the United States illegally via international mail. They are largely responsible for the overdose crisis in the United States, which has been declared a public health emergency. One factor contributing to the influx of these drugs is the low risk of detection when mailed in small quantities. The goal of our research is to slow the passage of synthetic opioids into the United States by developing a technology capable of detecting them in unopened packages using Nuclear Quadrupole Resonance (NQR) spectroscopy along with complex-valued and real-valued neural networks for signal denoising and classification to improve detection.

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