Summary
John Nardini is a postdoctoral scholar in Precision Medicine with a decade of experience applying mathematical models and machine learning to biological problems such as wound healing and cancer progression. He leverages differential equation modeling and statistical inference to translate experimental data into mechanistic insight, developed nonlinear diffusion models of epidermal cell migration, and analyzed biochemically-structured reaction–diffusion systems. Trained at University of Colorado Boulder (PhD, Applied Mathematics), he has a strong track record of interdisciplinary collaboration with biologists, chemists, and computer scientists to make models experimentally relevant. Beyond research, he’s an engaged educator who uses metacognitive strategies to help students overcome math anxiety, reflecting a rare blend of technical depth and communication skill. Based in Boulder, Colorado, he brings both theoretical rigor and practical focus to precision-medicine challenges.
10 years of coding experience
Doctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at University of Colorado Boulder