VIRTUAL: Department Seminar with Mathieu Bauchy: Decoding the Glass Genome by Machine Learning and Network Topology

Date(s) - 28 Sep 2020
3:00 PM - 4:00 PM


This is a webinar event.

Speaker: Mathieu Bauchy, Associate Professor of Civil and Environmental Engineering at the University of California, Los Angeles (UCLA)

Title: Decoding the Glass Genome by Machine Learning and Network Topology

Abstract: From windows to light bulbs, glass has played a pivotal role in human history. Today, optical glass fibers and touch-screen display glasses have changed the way humans interact with information. Glass also shows great promises to solve some of tomorrow’s grand challenges in healthcare or the environment. Addressing these challenges relies on the discovery of new glasses exhibiting unusual properties. However, since glasses can virtually accommodate the entire periodic table, with varying stoichiometry, traditional trial-and-error Edisonian discovery approaches are highly inefficient. Rather, accelerating the discovery of new glasses requires the “glass genome” to be decoded, that is, to identify and decipher how composition and structure (i.e., the glass “genes”) control glass’s engineering properties—in the same way as the human genome offers information that serves as a blueprint for an individual’s growth and development. In this presentation, I will present some of our recent effort in applying machine learning and topological modeling to decipher the glass genome and advance glass science & engineering.

Bio: Mathieu Bauchy is an Associate Professor in the Civil & Environmental Engineering Department at the University of California, Los Angeles (UCLA), where he runs the Physics of AmoRphous and Inorganic Solids Laboratory (PARISlab). He received his undergraduate education in physics at Ecole Normale Supérieure (France) before pursuing a Ph.D. in condensed matter at Université Pierre et Marie Curie (France). He then joined the Massachusetts Institute of Technology as a postdoctoral associate. Bauchy’s research focuses on decoding the physics governing the behavior of materials by means of simulations and machine learning. He received the Norbert J. Kreidl Award by the American Ceramics Society, the MDPI’s Materials Young Investigator, and the Elsevier’s Rising Star in Computational Materials Science Award. He has delivered more than 100 presentations and published more than 150 papers.

Seminar Host: Steve Martin

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