Nicholas D. Haynes, Research Assistant, Ph D Student
Office Location: 3539 FCIEMAS
Email Address: nicholas.haynes@duke.edu
Web Page: http://www.nickdhaynes.com
Specialties:
Nonlinear dynamics and complex systems
Education:
MS, University of Dayton, 2013
BS, University of Dayton, 2011
Research Categories: Complex networks for machine learning
Research Description: I'm an experimental physicist interested in the intersection of complex networks, machine learning, and the physics of information. I study how highly interconnected systems are able to store, transfer, and process information. Concretely, I build networks out of digital electronics on re-programmable integrated circuits called a field-programmable gate arrays (FPGAs). FPGAs are an invaluable tool for experimental network science because they allow us to design a network using a software environment but realize the circuit in physical hardware. I can then use these networks to perform a variety of fundamental and applied experiments, including teaching them to perform classification and regression tasks using state-of-the-art machine learning techniques. See my personal website for an up-to-date list of my current projects.
Areas of Interest:
Complex networks
Machine learning