Symposium MT03-Harnessing Data-Centric Strategies for Materials by Design

This symposium will cover the challenges in physics-driven intelligent materials discovery and design. This symposium will provide a forum for the community to evaluate and discuss the future of materials by design in an ever-evolving field driven by artificial intelligence and physics-informed computations/experiments. Topics of discussion will include challenges for which existing methods fail or remain inadequate, and up-and-coming areas of materials by design. These challenges will be considered both from the perspective of methodological/algorithmic developments and applications that leverage informatics/AI strategies as a primary component. Core topics will include physics-informed machine learning, data-centric strategies for AI in materials science, procedures for handling multi-model data/uncertainty, explainable and autonomous feature selection, interpretable machine learning and generalized explainable AI strategies, data pre-processing/augmentation strategies (particularly those related to generative modeling), and large language models. Emphasis will be placed on methods that bridge both length and time scales as well as methods that combine experiments and computations/simulations.

Topics will include:

Autonomous/explainable feature selection
Data preprocessing/augmentation
Physics aware/informed ML
Data-centric AI for materials
Uncertainty in both data and models
Procedures for combining data across datasets
Model interpretability
Large language models for materials discovery
Data strategies for generative models

Invited Speakers:

Brian Barnes (U.S. Department of the Army, USA)
Ramin Bostanabad (University of California, Irvine, USA)
Markus J. Buehler (Massachusetts Institute of Technology, USA)
Kamal Choudhary (National Institute of Standards and Technology, USA)
Payel Das (IBM T.J. Watson Research Center, USA)
Adji Bousso Dieng (Princeton University, USA)
Claudia Draxl (Humboldt-Universität Berlin, Germany)
Leora Dresselhaus-Marais (Stanford University, USA)
Saryu Fensin (Los Alamos National Laboratory, USA)
Luca Ghiringhelli (Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany)
Johannes Hachmann (University at Buffalo, The State University of New York, USA)
Anoop Krishnan (Indian Institute of Technology Delhi, India)
Santiago Miret (Intel Labs, USA)
Gian-Marco Rignanese (Université catholique de Louvain, Belgium)
Ellad Tadmor (University of Minnesota Twin Cities, USA)
Milica Todorovic (University of Turku, Finland)
Jinhui Yan (University of Illinois at Urbana-Champaign, USA)