Data Science for Materials Discovery
This lecture series explores combining modern data science approaches with material science, mechanical engineering, and biochemical problems to accelerate discovery and new applications. The webinar is part of the project "I-AIM: Interpretable Augmented Intelligence for Multiscale Materials Discovery" supported by the National Science Foundation.
The organizers are Wei Chen (IIT), Hendrik Heinz (CU Boulder, project lead), WaiChing Sun (Columbia U), Yusu Wang (UCSD) and Yanxun Xu (JHU).
I-AIM Seminar 14 (Michael Toney, CU Boulder), Data Challenges in X-ray Scattering, July 9, 2021
I-AIM Seminar 14 (Horacio Espinosa, Northwestern U), Machine Learning for Force Fields, Jun 25, 2021
I-AIM Seminar 12 (Nicholas Kotov, U Michigan), Graph Theory Descriptors for Composites, May 28, 2021
I-AIM Seminar 11 (John Miao, UCLA), Beyond Crystallography: CDI and AET, May 14, 2021
I-AIM Seminar 9 (Margaret Murnane, CU Boulder), Structure, Mechanics, Transport, April 16, 2021
I-AIM Seminar 8 (Yannis Kevrekidis, JHU), Free Energy Surface Exploration, April 02, 2021
I-AIM Seminar 7 (Arun Kumar, UCSD), Cerebro, March 19, 2021
I-AIM Seminar 6 (Wei Chen, NU), Data-Driven Design of Microstructural Material Systems, Feb 19, 2021
I-AIM Seminar 5 (Krishna Rajan) Dec18th
I-AIM seminar 4 (Kathryn Hess): From trees to barcode and back again
I-AIM Seminar 3 (Gunnar Carlsson): Topological data analysis (TD) and applications
I-AIM Seminar 1: Connecting data, algorithms and community in digital rock physics