Fall 2021 | Boston, MA
Charles Fisher is a scientist with interests at the intersection of physics, machine learning, and computational biology. Before founding Unlearn.AI to create artificial intelligence solutions that accelerate clinical research, Charles worked as a machine learning engineer at a Silicon Valley technology company and as a computational biologist at Pfizer. His research has spanned diverse areas including molecular simulations of protein folding, mathematical models of diverse ecosystems, and new approaches to machine learning with artificial neural networks. He was a Philippe Meyer Fellow in theoretical physics at École Normale Supérieure in Paris, France, and a postdoctoral scientist in biophysics at Boston University. Charles holds a Ph.D. in biophysics from Harvard University and a B.S. in biophysics from the University of Michigan.
DAY 1 /
Digital twins are AI-generated placebo patient data perfectly matched to actual trial patients. With a universal goal of being able to run better and faster clinical trials, this session will use an Alzheimer’s use case to demonstrate how digital twins can ultimately result in increased confidence in trial results.