Nathan joined the APPIL in May of 2023 as an undergraduate researcher. He has worked directly under the supervision of the PhD student, Soheil Hosseini, on creating segmentations of arterial and venous trees in 3D Dual energy CT Scans of Lungs. He has developed and trained convolutional neural networks to output automatic segmentations of the arterial and venous trees to find clinical relevance between vessel dysanapsis and various lung pathologies.

Nathan's professional interests include medical image processing, medical device design, medical device regulation, deep neural networks, and computer programming.