Dan Elton

About

Data scientist and machine learning engineer with a background in the hard sciences and deep experience in AI for medical imaging and healthcare. I am a co-author on over 50 peer-reviewed publications spanning physics, AI/ML for molecular discovery, and AI/ML for radiology. Here are a few I am most proud of: 📄 "Deep learning for molecular design—a review of the state of the art", 2019 (cited over 700 times) 📄 "Self-explaining AI as an alternative to interpretable AI" (Won the "best new AI idea" award at AGI-2020) 📄 "Opportunistic Screening at Abdominal CT: Use of Automated Body Composition Biomarkers for Added Cardiometabolic Value" - presents our vision for how medical AI can be used to obtain quantitative biomarkers from CT scans that can be used for disease risk prediction. 📄 "The hydrogen-bond network of water supports propagating optical phonon-like modes" - Nature Communications, 2016 📄 "The origin of the Debye relaxation in liquid water and fitting the high frequency excess response", 2016 - gives the full explanation for how water absorbs microwave radiation! Brief narrative: I grew up in the small town of Glens Falls, New York reading science fiction by authors like Isaac

Experience

Education