Ferguson’s research uses computation and theory to understand and design self-assembling materials, macromolecular folding, and antiviral therapies. In his materials work, he applies nonlinear manifold learning to all-atom and coarse-grained simulations of polymers, peptides, and colloids to determine folding and assembly mechanisms and rational design principles. In his virology work, he developed a statistical inference procedure to translate viral sequence databases into empirical models of fitness, and coupled these landscapes with models of host-pathogen interaction to perform computational design of vaccine immunogens against HIV and hepatitis C virus.

In his enhanced sampling work, he combines tools from dynamical systems theory and nonlinear manifold learning to recover folding landscapes from experimentally- accessible molecular observables, and uses tools from deep learning for on-the-fly collective variable identification and accelerated recovery of molecular free energy landscapes in molecular simulation.

Ferguson is the recipient of a 2017 UIUC College of Engineering Dean’s Award for Excellence in Research, 2016 AIChE CoMSEF Young Investigator Award for Modeling and Simulation, 2015 ACS OpenEye Outstanding Junior Faculty Award, 2014 NSF Career Award, 2014 ACS PRF Doctoral New Investigator, and was named the Institution of Chemical Engineers North America 2013 Young Chemical Engineer of the Year.