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Materials Science Seminar Series presents Dr. Mathew Cherukara on Thursday, September 21, from 4 to 5 p.m. The seminar is hosted by Professor Paul Evans and will be held in MS&E building room 265. Dr. Mathew Cherukara will be discussing High Performance Computing and Artificial Intelligence Enabled Materials Characterization and Experimental Automation.
The capabilities provided by next-generation light sources along with the development of new characterization techniques and detector advances are revolutionizing materials characterization (metrology) by providing the ability to perform scale-bridging, multi-modal materials characterization under in-situ and operando conditions. For example, providing the ability to image in 3D large fields of view (~mm ) at high resolution (<10 nm), while simultaneously acquiring information about structure, strain, elemental composition, oxidation state, photovoltaic response etc.
However, these novel capabilities dramatically increase the complexity and volume of data generated. Conventional data processing and analysis methods become infeasible in the face of such large and varied data streams. The use of AI/ML methods is becoming indispensable for real-time analysis, data abstraction and decision making at advanced, high-data rate instruments. I will describe how high-performance computing (HPC) along with AI on edge devices enables real-time data analysis and self-driving experiments, creating the next generation of AI-powered materials characterization tools.
Mathew Cherukara leads the Computational Science group at the Advanced Photon Source (APS) at Argonne National Laboratory. The group has 15 PhDs who develop algorithms, computational tools and AI/ML models to analyze and interpret data from the various x-ray characterization techniques performed at the APS. His personal research is in AI-enabled materials characterization, AI-guided autonomous experiments and AI-accelerated materials modeling. He has particular interest in the development of novel x-ray and electron imaging capabilities that are only made possible because of AI. Mathew received his Ph.D from Purdue University in 2015 in computational materials science and his bachelors from the Indian Institute of Technology (IIT) Madras in 2010. He has 4 patents and has published over 60 peer-reviewed papers.