Education and Research Experience

Education

The University of Chicago

The Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, Sept. 2023 – Present

Argonne National Laboratory

Resident Associate (Host: Junhong Chen), Sept. 2023 – Present

Advisors

• Junhong Chen, Prof. Dr. (The University of Chicago-Pritzker School of Molecular Engineering; Argonne National Laboratory)
• Yuxin Chen, Prof. Dr. (The University of Chicago-Department of Computer Science)

Research Experience

Summary of Research Work at UChicago/Argonne (Sept. 2023 – Present)

• Proposed the 'Broad-scope Reasoning Artificial Intelligence for Nano-micro material and devices Identification, Assessment, and Categorization' (BRAINIAC) Project, which focuses on enhancing materials discovery and device innovation using advanced data collection and machine learning in collaborative experimental frameworks.
• BRAINIAC aims to integrate a vast multi-fidelity dataset with sophisticated graph neural networks. BRAINIAC supports the identification and optimization of materials for various applications, typically including sensors and catalysts for renewable energy and environmental science. The project also fosters a collaborative scientific community, enabling continuous improvement and widespread adoption of AI-driven methodologies.
• Participate in the NSF-funded Manufacturing ADvanced Electronics through Printing Using Bio-based and Locally Identifiable Compounds (MADE-PUBLIC) Project as the Designer of the Data Portal to Facilitate Knowledge Transfer as well as a cyber-manufacturing platform.

Conference Presentations

1. Rui Ding (2024) Hunting for Rare High-Performance Electrocatalysts: A Multi-Stage ML Approach to Discover Extreme Performers in Acidic Oxygen Evolution NSF Workshop on Data-driven Modeling and Prediction of Rare and Extreme Events, University of Chicago, Chicago, Illinois, United States
2. Rui Ding (2024) Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts Al for Multidisciplinary Exploration and Discovery Workshop-Heterogeneous Catalysis, Big Ten Conference Center, Rosemont, Illinois, United States
3. Rui Ding (2024) Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts AI+Science Summer School 2024, University of Chicago, Chicago, Illinois, United States
4. Rui Ding (2024) Cybermanufacturing Platform of MADE-PUBLIC Project NSF Future Manufacturing Research Grant on Manufacturing ADvanced Electronics through Printing Using Bio-based and Locally Identifiable Compounds (MADE-PUBLIC) Annual Retreat 2024, Northwestern University, Evanston, Illinois, United States
5. Rui Ding (2024) One of the University of Chicago host representatives for visiting speaker scholars 2024 AI+ Science Schmidt Fellows Speaker Series at University of Chicago