{"688223":{"#nid":"688223","#data":{"type":"news","title":"Department of Energy Award to Power Nuclear Research With Machine Learning","body":[{"value":"\u003Cp\u003EThe future of clean energy depends on algorithms as much as it does atoms.\u003C\/p\u003E\u003Cp\u003EGeorgia Tech\u2019s\u0026nbsp;\u003Ca href=\u0022https:\/\/cse.gatech.edu\/people\/qi-tang\u0022\u003E\u003Cstrong\u003EQi Tang\u003C\/strong\u003E\u003C\/a\u003E is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy (DOE), Tang\u2019s work brings clean, sustainable energy closer to reality.\u003C\/p\u003E\u003Cp\u003ETang has received an\u0026nbsp;\u003Ca href=\u0022https:\/\/science.osti.gov\/early-career\u0022\u003E\u003Cstrong\u003EEarly Career Research Program (ECRP) award\u003C\/strong\u003E\u003C\/a\u003E from the DOE Office of Science. The grant supports Tang with $875,000 disbursed over five years to craft ML and data processing tools that help scientists analyze massive datasets from nuclear experiments and simulations.\u003C\/p\u003E\u003Cp\u003ETang is the first faculty member from Georgia Tech\u2019s College of Computing and School of Computational Science and Engineering (CSE) to receive the ECRP. He is the seventh Georgia Tech researcher to earn the award and the only GT awardee among this year\u2019s 99 recipients.\u003C\/p\u003E\u003Cp\u003EMore than a milestone, the award reflects a shift in how nuclear research is done. Today, progress depends on computing and data science as much as on physics and engineering.\u003C\/p\u003E\u003Cp\u003E\u201cI am honored and excited to receive the ECRP award through DOE\u2019s Advanced Scientific Computing Research program, an organization I care about deeply,\u201d said Tang, an assistant professor in the School of CSE.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cI am grateful to my former colleagues at Los Alamos National Laboratory and collaborators at other national laboratories, including Lawrence Livermore, Sandia, and Argonne. I am also thankful for my Ph.D. students at Georgia Tech, whose dedication and creativity make this award possible.\u201d\u003C\/p\u003E\u003Cp\u003E[Related:\u0026nbsp;\u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/news\/new-faculty-applies-high-performance-computing-scientific-machine-learning-interests-studies\u0022\u003E\u003Cstrong\u003ENew Faculty Applies High-Performance Computing, Scientific Machine Learning Interests to Studies in Plasma Physics\u003C\/strong\u003E\u003C\/a\u003E]\u003C\/p\u003E\u003Cp\u003EA problem in nuclear research is that fusion simulations are challenging to understand and use. These simulations generate enormous datasets that are too large to store, move, and analyze efficiently.\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/pamspublic.science.energy.gov\/WebPAMSExternal\/Interface\/Common\/ViewPublicAbstract.aspx?rv=a756f612-3409-44b8-89ea-7421bf0840e5\u0026amp;rtc=24\u0026amp;PRoleId=10\u0022\u003E\u003Cstrong\u003EIn his ECRP proposal to DOE\u003C\/strong\u003E\u003C\/a\u003E, Tang introduced new ML methods to improve the analysis and storage of particle data.\u003C\/p\u003E\u003Cp\u003ETang\u2019s approach balances shrinking data so it is easier to store and transfer while preserving the most important scientific features. His multiscale ML models are informed by physics, so the reduced data still reflects how fusion systems really behave.\u003C\/p\u003E\u003Cp\u003EWith Tang\u2019s research, scientists can run larger, more realistic fusion models and analyze results more quickly. This accelerates progress toward practical fusion energy.\u003C\/p\u003E\u003Cp\u003E\u201cIn contrast to generic black-box-type compression tools, we aim at preserving the intrinsic structures of the particle dataset during the data reduction processes,\u201d Tang said.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cTaking this approach, we can meet our goal of achieving high-fidelity preservation of critical physics with minimum loss of information.\u201d\u003C\/p\u003E\u003Cp\u003EComputing is essential in modern research because of the amount of data produced and captured from experiments and simulations. In the era of exascale supercomputers, data movement is a greater bottleneck than actual computation.\u003C\/p\u003E\u003Cp\u003EDOE operates three of the world\u2019s four exascale supercomputers. These machines can calculate one quintillion (a billion billion) operations per second.\u003C\/p\u003E\u003Cp\u003EThe exascale era began in 2022 with the launch of Frontier at Oak Ridge National Laboratory. Aurora followed in 2023 at Argonne National Laboratory. El Capitan arrived in 2024 at Lawrence Livermore National Laboratory.\u003C\/p\u003E\u003Cp\u003EWith Tang\u2019s data reduction approaches, all of DOE\u2019s supercomputers spend more time on science and less time waiting for data transfers.\u003C\/p\u003E\u003Cp\u003E\u201cQi\u2019s work in computational plasma physics and nuclear fusion modeling has been groundbreaking,\u201d said \u003Cstrong\u003EHaesun Park\u003C\/strong\u003E, Regents\u2019 Professor and Chair of the School of CSE.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cWe are proud of Qi and what this award means for him, Georgia Tech, and the Department of Energy toward leveraging computation to solve challenges in science and engineering, such as sustainable energy.\u0022\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch6\u003E\u003Cstrong\u003EPrevious Georgia Tech recipients of DOE Early Career Research Program awards include:\u003C\/strong\u003E\u003C\/h6\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.gatech.edu\/news\/2024\/09\/26\/doe-recognizes-georgia-tech-researchers-prestigious-early-career-awards\u0022\u003E\u003Cstrong\u003EItamar Kimchi\u003C\/strong\u003E\u003C\/a\u003E, assistant professor, School of Physics\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.gatech.edu\/news\/2024\/09\/26\/doe-recognizes-georgia-tech-researchers-prestigious-early-career-awards\u0022\u003E\u003Cstrong\u003ESourabh Saha\u003C\/strong\u003E\u003C\/a\u003E, assistant professor, George W. Woodruff School of Mechanical Engineering\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/cos.gatech.edu\/news\/wenjing-liao-awarded-doe-early-career-award-model-simplification-deep-learning\u0022\u003E\u003Cstrong\u003EWenjing Lao\u003C\/strong\u003E\u003C\/a\u003E, associate professor, School of Mathematics\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/chbe.gatech.edu\/news\/2018\/06\/professor-lively-receives-does-early-career-award\u0022\u003E\u003Cstrong\u003ERyan Lively\u003C\/strong\u003E\u003C\/a\u003E, Thomas C. DeLoach Professor, School of Chemical \u0026amp; Biomolecular Engineering\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.mse.gatech.edu\/people\/josh-kacher\u0022\u003E\u003Cstrong\u003EJosh Kacher\u003C\/strong\u003E\u003C\/a\u003E, associate professor, School of Materials Science and Engineering\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/khabar.com\/community-newsmakers\/devesh-ranjan-receives-early-career-award-from-u-s-department-of-energy\/\u0022\u003E\u003Cstrong\u003EDevesh Ranjan\u003C\/strong\u003E\u003C\/a\u003E, Eugene C. Gwaltney Jr. School Chair and professor, Woodruff School of Mechanical Engineering\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech\u2019s\u0026nbsp;\u003Ca href=\u0022https:\/\/cse.gatech.edu\/people\/qi-tang\u0022\u003EQi Tang\u003C\/a\u003E is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy (DOE), Tang\u2019s work brings clean, sustainable energy closer to reality.\u003C\/p\u003E\u003Cp\u003ETang has received an\u0026nbsp;\u003Ca href=\u0022https:\/\/science.osti.gov\/early-career\u0022\u003EEarly Career Research Program (ECRP) award\u003C\/a\u003E from the DOE Office of Science. The grant supports Tang with $875,000 disbursed over five years to craft ML and data processing tools that help scientists analyze massive datasets from nuclear experiments and simulations.\u003C\/p\u003E\u003Cp\u003ETang is the first faculty member from Georgia Tech\u2019s College of Computing and School of Computational Science and Engineering (CSE) to receive the ECRP. He is the seventh Georgia Tech researcher to earn the award and the only GT awardee among this year\u2019s 99 recipients.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Tech\u0027s Qi Tang has received an Early Career Research Program award from the Department of Energy\u0027s Office of Science. The $875,000 grant supports Tang for five years to craft ML tools that analyze data from nuclear experiments and simulations. "}],"uid":"36319","created_gmt":"2026-02-12 15:11:55","changed_gmt":"2026-03-20 12:52:31","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-02-12T00:00:00-05:00","iso_date":"2026-02-12T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679267":{"id":"679267","type":"image","title":"Qi-TangStory-Cover.jpg","body":null,"created":"1770909124","gmt_created":"2026-02-12 15:12:04","changed":"1770909124","gmt_changed":"2026-02-12 15:12:04","alt":"DOE ECRP Qi Tang","file":{"fid":"263400","name":"Qi-TangStory-Cover.jpg","image_path":"\/sites\/default\/files\/2026\/02\/12\/Qi-TangStory-Cover.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/02\/12\/Qi-TangStory-Cover.jpg","mime":"image\/jpeg","size":125283,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/02\/12\/Qi-TangStory-Cover.jpg?itok=mPLUykJZ"}}},"media_ids":["679267"],"related_links":[{"url":"https:\/\/www.cc.gatech.edu\/news\/department-energy-award-power-nuclear-research-machine-learning","title":"Department of Energy Award to Power Nuclear Research with Machine Learning"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1188","name":"Research Horizons"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"153","name":"Computer Science\/Information Technology and Security"},{"id":"144","name":"Energy"},{"id":"135","name":"Research"}],"keywords":[{"id":"654","name":"College of Computing"},{"id":"166983","name":"School of Computational Science and Engineering"},{"id":"9153","name":"Research Horizons"},{"id":"187915","name":"go-researchnews"},{"id":"10199","name":"Daily Digest"},{"id":"181991","name":"Georgia Tech News Center"},{"id":"9167","name":"machine learning"},{"id":"2556","name":"artificial intelligence"},{"id":"187812","name":"artificial intelligence (AI)"},{"id":"663","name":"Department of Energy"}],"core_research_areas":[{"id":"193655","name":"Artificial Intelligence at Georgia Tech"},{"id":"39431","name":"Data Engineering and Science"},{"id":"39531","name":"Energy and Sustainable Infrastructure"}],"news_room_topics":[{"id":"71871","name":"Campus and Community"}],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EBryant Wine, Communications Officer\u003Cbr\u003E\u003Ca href=\u0022mailto:bryant.wine@cc.gatech.edu\u0022\u003Ebryant.wine@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}