Materials Science and Engineering Special Seminar


Andrew Ferguson, Dept. of Materials Science and Engineering, University of Illinois at Urbana-Champaign

Date Mon, 09/18/2017

100 Materials Science and Engineering Building

Time 4:00 pm

Materials Science and Engineering

Event Type Seminar/Symposium

 "Machine learning in soft and biological materials: Engineering self-assembling colloids and viral phase behavior" 


Data-driven modeling and machine learning have opened new paradigms and opportunities in the understanding and design of soft and biological materials. Colloidal particles with tunable anisotropic surface interactions are of technological interest in fabricating soft responsive actuators, biomimetic polyhedral encapsulants, and substrates for high-density information storage. In the first part of this talk, I will describe our applications of nonlinear manifold learning to determine low-dimensional assembly landscapes for self-assembling patchy colloids. These landscapes connect colloid architecture and prevailing conditions with emergent assembly behavior, and enable inverse building block design by rational sculpting of the landscape to engineer the stability and accessibility of desired aggregates. Empirical models of viral fitness present a means to rationally design antiviral therapeutics by revealing vulnerabilities within the viral proteome. In the second part of this talk, I will discuss the translation of clinical sequence databases into spin glass models of viral fitness. These data-driven fitness models reveal an intimate connection with statistical thermodynamics in which HIV sustains an "error catastrophe" – mutational meltdown of the viral quasispecies induced by an elevated mutation rate – isomorphic to a first order phase transition. Our work informs new antiviral control strategies and provides a rationale for why HIV can live on the precipice of the error catastrophe with impunity.