Nick's research draws inspiration from biological systems to design machine learning algorithms for artificial neural networks. This involves creating more flexible, scalable, and context-aware robots and decision-making systems through a variety of techniques like deep learning, reinforcement learning, evolutionary computation, and meta-learning. Nick is currently a Research Assistant Professor in Computer Science. Prior to that he studied Applied Mathematics at UVM and received his Ph.D. from Cornell, studying Computational Biology under Hod Lipson and Steve Strogatz, while also serving as a research fellow at NASA.
Research Assistant, Professor
- Ph.D. Computational Biology, Cornell University
- B.S. Applied Mathematics, University of Vermont