{"id":3965,"date":"2026-03-09T11:10:26","date_gmt":"2026-03-09T16:10:26","guid":{"rendered":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/?post_type=tribe_events&p=3965"},"modified":"2026-03-09T11:10:26","modified_gmt":"2026-03-09T16:10:26","slug":"lans-seminar-195","status":"publish","type":"tribe_events","link":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/event\/lans-seminar-195\/","title":{"rendered":"LANS Seminar"},"content":{"rendered":"

Seminar Title<\/strong>: What We are Building in GridAI: GridMind, LUMINA, and APPFL<\/span><\/p>\n

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Speaker<\/strong>: Kibaek Kim, Computational Mathematician, Laboratory for Applied Mathematics, Numerical Software, and Statistics, Mathematics and Computer Science Division, Argonne National Laboratory, and a Senior Scientist at-Large, University of Chicago Consortium for Advanced Science and Engineering<\/p>\n

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Date:<\/strong> Thursday, March 12, 2026<\/p>\n

Time:<\/strong>\u00a02:30 PM-3:30 PM (In-Person)<\/p>\n

Location:<\/strong>\u00a0Hybrid, Bldg. 240, Conference Room 4301<\/p>\n

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Description<\/strong>: GridAI is one of the DOE Genesis Mission seed Model Team projects, with a focus on advancing the electric grid operations and planning with AI. This seminar gives a technical, work-in-progress view of what we are building at Argonne for GridAI, organized around a concrete use case: contingency analysis under a hurricane event on a synthetic Texas\u00a0system. I will briefly introduce GridMind as the agentic workflow component that coordinates tools, models, and simulations, then focus mainly on LUMINA: the foundation-model training and inference pipeline, what we observe empirically in experiments, and how we integrate surrogate inference with selective calls to high-fidelity solvers when needed. I will also touch on APPFL and recent results that enable distributed training\/adaptation across HPC facilities. I will close with a forward-looking vision for GridAI with these capabilities: scalable, AI-enabled grid analysis that moves from fragmented studies to proactive risk identification and end-to-end decision support in collaboration with other labs and partners.<\/p>\n

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Bio: <\/b>I am a Computational Mathematician in the Laboratory for Applied Mathematics, Numerical Software, and Statistics within the Mathematics and Computer Science Division at Argonne National Laboratory, and a Senior Scientist at-Large at the University of Chicago Consortium for Advanced Science and Engineering. My research focuses on federated learning algorithms and open-source software, agentic workflow orchestration for large-scale scientific and engineering studies, and modeling and numerical algorithms for optimization on high-performance computing systems and GPUs. My work is applied to electric power system operations and planning (e.g., large-scale contingency analysis and fast surrogate screening), healthcare, and other scientific domains of interest to the U.S. Department of Energy. Before joining Argonne, I obtained a Ph.D. degree in Industrial Engineering and Management Sciences from Northwestern University. I am a recipient of the DOE Early Career Research Program award. I serve as an associate editor for Mathematical Programming Computation and Naval Research Logistics, and as a board member for the COIN-OR Foundation and IISE Energy Systems.<\/p>\n

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Please note that the meeting URL for this event can be seen on the cels-seminars website which requires an Argonne login.<\/em><\/p>\n

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See all upcoming talks at\u00a0https:\/\/www.anl.gov\/mcs\/lans-seminars<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Seminar Title: What We are Building in GridAI: GridMind, LUMINA, and APPFL   Speaker: Kibaek Kim, Computational Mathematician, Laboratory for Applied Mathematics, Numerical Software, and Statistics, Mathematics and Computer Science Division, Argonne National Laboratory, and a Senior Scientist at-Large, University … Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":976,"featured_media":0,"template":"","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[2],"class_list":["post-3965","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-seminar","cat_seminar"],"acf":[],"_links":{"self":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events\/3965","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/users\/976"}],"version-history":[{"count":2,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events\/3965\/revisions"}],"predecessor-version":[{"id":3968,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events\/3965\/revisions\/3968"}],"wp:attachment":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/media?parent=3965"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tags?post=3965"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events_cat?post=3965"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}