Zan is a PhD student in Systems Biology (SSQB) at Harvard interested in spanning the extremes of large, overparametrized models such as neural networks and small, interpretable models such as differential equations. His central goal is combining predictive/generative power with first-principles mechanistic understanding to map and decipher aging at multiple scales, from single cell omics data to electronic health records. He is originally from Minnesota, received a B.S. in Biomedical Engineering from Johns Hopkins University. At JHU, he began in neural engineering research in the Thakor Lab, focused on sensory feedback in prosthetics then later joined the Radiology AI Lab, developing anomaly and mislabeled data detection methods using neural network feature spaces. He also spent a summer at AstraZeneca, working on ML methods for post-translational modification prediction in drug candidates. At the NIH, he worked on theory-motivated methods for autonomous machine learning pipelines and cryo-ET for sickle cell biology. Outside of the lab, Zan enjoys exploring with his wife and two dogs, playing/writing music, and playing basketball.
Sun Lab