Summary
Nick Konz is a postdoctoral researcher and machine learning scientist with eight years of experience developing novel ML methods for medical image analysis and AI for science. Currently at UNC Chapel Hill's UNITES Lab, he works on agentic and multimodal AI for healthcare and protein/genomic language modeling, bridging clinical impact with foundational science. His PhD work at Duke uncovered how neural networks learn differently from medical versus natural images and produced practical tools for guided medical image generation, domain adaptation, and self-supervised anomaly detection. He is a prolific reproducible researcher who prioritizes public releases—his code and datasets have attracted hundreds of GitHub stars and accompany multiple first-author publications in ICLR, MICCAI, MIDL, and Medical Image Analysis. Beyond modeling, he has taught deep learning courses, contributed to ML robustness and interpretability research presented at NeurIPS/EMNLP workshops, and brings a background in physics and computational astronomy to interdisciplinary problems. Colleagues value him for rigorous experimentation, clear open-source artifacts, and a knack for turning complex medical imaging challenges into usable research tools.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Electrical and Computer Engineering, Doctor of Philosophy - PhD Electrical and Computer Engineering at Duke University
Bachelor of Science - BS Physics and Mathematics, Bachelor of Science - BS Physics and Mathematics at The University of North Carolina at Chapel Hill
High School Diploma, High School Diploma at Asheville High School
English