{"690900":{"#nid":"690900","#data":{"type":"news","title":"Xiaoming Huo Recognized with Outstanding Mid-Career\/Senior Faculty Achievement in Research Award","body":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/xiaoming-huo\u0022\u003EXiaoming Huo\u003C\/a\u003E has received the \u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/\u0022\u003EH. Milton Stewart School of Industrial and Systems Engineering\u2019s (ISyE)\u003C\/a\u003E Outstanding Mid-Career\/Senior Faculty Achievement in Research Award. The honor annually recognizes a faculty member for their research impact and is based on publication quality and quantity, citations, awards, and the translation of methods into practice.\u003C\/p\u003E\u003Cp\u003EAs ISyE\u2019s A. Russell Chandler III Professor, Huo\u2019s theoretical research focuses on explaining why modern deep-learning methods preform so well. He also uses statistics, machine learning, and data science to better to better understand the reliability and fairness of learning systems.\u003C\/p\u003E\u003Cp\u003EHuo has authored more than 15 refereed journal articles since 2023 and currently has 10 papers under review. His career includes 71 journal articles, 41 conference papers, 10 book chapters, and an edited volume.\u003C\/p\u003E\u003Cp\u003E\u201cWhat I find most rewarding is that rigorous theory and useful tools are not in tension \u2013 the mathematical questions that fascinate me most often turn out to be the ones that help others make sense of their data,\u201d Huo said. \u201cI\u2019m deeply honored to receive this award and especially grateful to my students and collaborators, who have been at the heart of this work from the very beginning.\u201d\u003C\/p\u003E\u003Cp\u003EHuo\u2019s first algorithm for distance covariance remains a standard tool for testing statistical dependence and is reproduced in widely used statistical software. He co-directs the \u003Ca href=\u0022https:\/\/georgiactsa.org\/\u0022\u003EGeorgia Clinical and Translational Science Alliance\u003C\/a\u003E\u0027s \u003Ca href=\u0022https:\/\/georgiactsa.org\/research\/berd\/index.html\u0022\u003EBiostatistics, Epidemiology and Research Design\u003C\/a\u003E program, which is supported by the \u003Ca href=\u0022https:\/\/www.nih.gov\/\u0022\u003ENational Institutes of Health\u003C\/a\u003E. He also serves as a co-principal investigator on the $20 million \u003Ca href=\u0022https:\/\/aiinstitutes.org\/institute-action\/\u0022\u003ENSF AI Institute for Agent-based Cyber Threat Intelligence and Operation\u003C\/a\u003E.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EHuo said he is proud of the researchers he has trained. In the most recent recruiting cycle, his doctoral graduates earned tenure-track faculty offers from Georgetown University and the University of Florida. Earlier advisees hold faculty positions at the City University of Hong Kong, Korea Advanced Institute of Science and Technology, and Seoul National University of Science and Technology, while other former students are researchers at companies that include Apple, Citadel, and JP Morgan.\u003C\/p\u003E\u003Cp\u003EHis recently published work includes \u003Ca href=\u0022https:\/\/www.jmlr.org\/papers\/v25\/23-0957.html\u0022\u003Etwo\u003C\/a\u003E 2024 papers in the \u003Ca href=\u0022https:\/\/www.jmlr.org\/papers\/v25\/23-0379.html\u0022\u003EJournal of Machine Learning Research \u003C\/a\u003E(\u003Ca href=\u0022https:\/\/www.jmlr.org\/\u0022\u003EJMLR\u003C\/a\u003E). He and his students established learning guarantees for deep neutral networks, including minimax-optimal convergence rates of neural-network classifiers was accepted in 2026 by \u003Ca href=\u0022https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=11352993\u0022\u003EIEEE Transactions on Information Theory\u003C\/a\u003E, and his work on the universal consistency of wide and deep networks appeared at the International Conference on Machine Learning. \u0026nbsp;\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EHuo\u2019s work on the fairness of learning systems is reflected in a \u003Ca href=\u0022https:\/\/datasetcatalog.nlm.nih.gov\/dataset?q=0002031630\u0022\u003E2025 Journal of the American Statistical Association paper\u003C\/a\u003E that characterizes the asymptotic behavior of the adversarial-training estimator, complementing his JMLR work on distributionally robust estimation. At the \u003Ca href=\u0022https:\/\/neurips.cc\/Conferences\/2025\u0022\u003EConference on National Information Processing Systems (NeurIPS) 2025\u003C\/a\u003E, Huo and collaborators introduced a kernel-based quantification of the accuracy fairness trade-off in representation learning, along with a new diffusion method for imbalanced text-to-image generation, while a 2026 International Conference on Learning Representations paper advanced policy optimization for large-language-model reasoning.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe honor annually recognizes a faculty member for their research impact and is based on publication quality and quantity, citations, awards, and the translation of methods into practice.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"The honor annually recognizes a faculty member for their research impact and is based on publication quality and quantity, citations, awards, and the translation of methods into practice."}],"uid":"36760","created_gmt":"2026-06-24 16:05:20","changed_gmt":"2026-06-26 17:34:27","author":"jsmith830","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-06-24T00:00:00-04:00","iso_date":"2026-06-24T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"680505":{"id":"680505","type":"image","title":"Xiaoming Huo, A. Russell Chandler III Professor ","body":"\u003Cp\u003EXiaoming Huo, A. Russell Chandler III Professor\u0026nbsp;\u003C\/p\u003E","created":"1782317685","gmt_created":"2026-06-24 16:14:45","changed":"1782317685","gmt_changed":"2026-06-24 16:14:45","alt":"Xiaoming Huo, A. Russell Chandler III Professor ","file":{"fid":"264778","name":"Professor-Huo-Square.jpg","image_path":"\/sites\/default\/files\/2026\/06\/24\/Professor-Huo-Square.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/06\/24\/Professor-Huo-Square.jpg","mime":"image\/jpeg","size":166602,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/06\/24\/Professor-Huo-Square.jpg?itok=86UQcDa3"}}},"media_ids":["680505"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[{"id":"135","name":"Research"}],"keywords":[{"id":"187915","name":"go-researchnews"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}