AI for Advanced Materials Design

Symposium Co-Chairs

Peter Koenig
Group Head
Procter & Gamble

Rick Ross
Lead Research Specialist
3M Company

Key Speakers

Closed-loop autonomous combinatorial experimentation for streamlined materials discovery
Ichiro Takeuchi
Professor, University of Maryland

The combination of data-driven and physics-based modeling with application in protein formulations.
Hans Fraaije
Chief Science Advisor
Siemens, Netherlands

Back to Top ↑ 2021 Symposium Sessions
	Tuesday October 19
10:30	Molecular Modeling
	Wednesday October 20
8:30	AI Track Keynote
10:30	AI for Advanced Materials Discovery & Design

2021 Symposium Program
	Tuesday October 19

10:30	Molecular Modeling	Baltimore 4
	Session chair: Peter Koenig, Procter & Gamble
10:30	Combining Physics-based models with Bayesian methods in a Small-data world for Product Development S. Jamadagni, Procter & Gamble, US
10:55	Combining theory and simulations with experiments for design and characterization of macromolecular materials A. Jayaraman, University of Delaware, US
11:20	Coarse-grain models of polymer melts: Preserving structure and dynamics L.C. Johnson, F.R. Phelan Jr., National Institute of Standards and Technology, US
11:40	Stokesian Particle Dynamics for microrheology applications between chemistry and engineering J.G.E.M. Fraaije, Siemens Culgi, NL
	Wednesday October 20

8:30	AI Track Keynote	Woodrow Wilson D
	Session chair: Richard Ross, 3M Company & Peter Koenig, Procter & Gamble
8:30	Closed-loop autonomous combinatorial experimentation for streamlined materials discovery I. Takeuchi, University of Maryland, US
9:00	From atoms to emergent mechanisms with information bottleneck and diffusion probabilistic models P. Tiwary, University of Maryland, US
9:30	Deep Learning for Linking Chemical and Biological Space in Small Molecules and Macromolecules A. Shehu, George Mason University, US

10:30	AI for Advanced Materials Discovery & Design	Annapolis 2
	Session chair: Richard Ross, 3M Company & Peter Koenig, Procter & Gamble
10:30	The combination of data-driven and physics-based modeling with application in protein formulations J.G.E.M. Fraaije, P. Petris, Siemens Culgi, NL
10:55	Next Generation PCIe Network Fabric for Simulators and Performance Computing C.T. Reynolds, Technical Systems Integrators, US
11:15	AI-accelerated materials innovation: From Optoelectronics to Fluorescent Biomarkers C. Kreisbeck, Kebotix, US
11:35	Machine Learning for the Exploration of Nanomaterial Synthesis Parameter Spaces R. Sappington, B. Cornick, Epic Advanced Materials, US
11:55	A Self-Driving Laboratory for Accelerated Materials Discovery C.P. Berlinguette, J.E. Hein, A. Aspuru-Guzik, B.P. MacLeod, F.G.L. Parlane, University of British Columbia, CA