Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

NSF Lecture- Soft Materials Research in the Era of Machine Learning

December 4th, 2017 / in Announcements, NSF, policy, research horizons, Research News / by Helen Wright

National Science Foundation (NSF) [credit: NSF]Professor Juan de Pablo from the Institute for Molecular Engineering at University of Chicago will be giving a lecture on Soft Materials Research in the Era of Machine Learning at the National Science Foundation (NSF) on Monday, December 11th at 2:00-3:00PM ET. 

Juan de Pablo is the Liew Family Professor and Deputy Director for Education and Outreach of the Institute for Molecular Engineering at the University of Chicago.  He earned his BChE from the Universidad Nacional Autónoma de México, and his PhD in Chemical Engineering at the University of California, Berkeley. He conducted postdoctoral research at the Swiss Federal Institute of Technology (ETH) in Zurich and joined the faculty of the University of Wisconsin–Madison in 1992, where he was Distinguished Professor of Chemical Engineering before joining the University of Chicago in 2012.

Prof. de Pablo is the 2018 winner of the American Physical Society’s Polymer Prize. He received the DuPont Medal for Excellence in Nutrition and Health Sciences in 2016, the Intel Patterning Science Award in 2015, and the Charles Stine Award from the American Institute of Chemical Engineers in 2011. He was inducted into the National Academy of Engineering in 2016 and is a Fellow of the American Academy of Arts and Sciences and of the American Physical Society.  He was also elected as Foreign Correspondent Member of the Mexican Academy of Sciences in 2014. He currently chairs the Committee on Condensed Matter and Materials Research at the National Research Council and is the founding editor of Molecular Systems Design and Engineering.


The advent of innovative molecular modeling algorithms, optimization strategies, and machine learning techniques is ushering a new era of molecular engineering in which computational tools are routinely used to probe, design, and interrogate materials and functional materials systems. In this presentation Prof. de Pablo will illustrate some of these ideas in the context of a variety of examples taken from chemical engineering, physics, biology, and materials science.

Using advanced multiscale simulation techniques and powerful computers, the de Pablo group seeks to predict the properties of fluids and solids from a fundamental understanding of molecular interactions across multiple length scales. The group’s interests encompass materials behavior at equilibrium and far-from-equilibrium. Building on that atomic and molecular-level understanding, the group relies on sophisticated computational algorithms to design functional materials systems with engineered structures and functions.

The lecture will be in Room E3410, 3rd floor, National Science Foundation, 2415 Eisenhower Ave., Alexandria, VA 22314 (across from Eisenhower Metro). Visitors must please contact Andrew Lovinger,, in advance to arrange for a visitor pass and should consult the Visit NSF information.

NSF Lecture- Soft Materials Research in the Era of Machine Learning