The vision of the MDS3 COE is to develop, demonstrate, and deploy novel Data Science tools, frameworks, codes, and computing infrastructure to advance our understanding of Materials degradation and the failure of materials, components, and subsystems using novel computer science and data sciencewhile empowering current NNSA employees and delivering a pipeline of the diverse, data-enabled workforce for the future. Phase II of the MDS3 COE will integrate the developed knowledge and workflows across the programs and agencies of the NNSA.

There will be four research thrusts and one workforce thrust in the MDS3 COE. The Research Thrusts include Computing Infrastructure, Knowledge Management & Learning, Field-Lab Aging & Reliability, and Next Generation Component Design & Production. 

Dr. Mondal will be leading the Knowledge Management & Learning research thrust which will focus on developing scalable and privacy-preserving knowledge modeling and learning techniques. This includes developing a robust statistical learning framework for computer experiments, with the goal of developing both theoretical and methodological tools that cover the typical computer simulation pipeline and quantify the uncertainties in the estimation method.

Faculty: Anirban Mondal
Agency: National Nuclear Security Administration (NNSA) – Department of Energy (DOE) 
Funding Amount: $14,200, 000 for Phase I, Duration: 09/15/2022 – 09/14/2027
Role: Co-I, PI – Roger French

CWRU daily: https://thedaily.case.edu/case-western-reserve-wins-14-2-million-federal-grant-to-launch-innovative-materials-data-science-center-of-excellence/
Energy.gov: https://www.energy.gov/nnsa/articles/nnsa-awards-14-million-materials-research-case-western-reserve-university

Faculty: Anirban Mondal
Agency: Simons Foundation
Project Title: Bayesian uncertainty quantification in remote sensing and infectious disease
modeling, and robust statistical methods in variable selection and clustering
Funding Amount: $42000, Duration: 09/012022-08/31/2027, Role: PI