Yao Xie 谢瑶
Email: yao.c.xie@gmail.com, or yao.xie@isye.gatech.edu ResearchMy research develops the statistical and computational foundations for sequential inference and change-point detection, robust decision-making under uncertainty, and modern generative modeling. I work at the intersection of statistics, optimization, and machine learning to create methods that are both powerful and efficient for high-dimensional, structured, and spatio-temporal data, with strong theoretical guarantees, and real-world applications in public safety, power grids, and health and biomedical systems. My work has generated societal and policy impact, including contributions to data-driven policing. Media and institutional coverage of my research includes:
Major Honors and Distinctions
Currently TeachingUndergraduate course: ISyE 4600, Methods and Applications of Machine Learning. Fall 2025. UpdatesTechnical Program Co-Chair, 2026 IEEE Information Theory Workshop. Serving as an INFORMS 2025 Tutorials Co-chair. Co-organizing NeurIPS 2025 Workshop, ML x OR: Mathematical Foundations and Operational Integration of Machine Learning for Uncertainty-Aware Decision-Making. Serving on Advisory Board for DASS Program, UK, 2024-2029. August 2026, give lectures at NSF Workshop on the Intersection of Statistics and Engineering, at University of Pennsylvania. June 2026, talk at Seventh IMS Asia Pacific Rim Meeting (IMS-APRM), Hong Kong. June 2026, talk and organize sessions at the 9th International Workshop in Sequential Methodologies (IWSM), Washington DC. May 2026, talk at ASA/IMS Spring Research Conference (SRC). May 2026, MIT Operations Research Seminar. March 2026, Columbia University, IEOR Seminar. March 2026, talk at SIAM Conference on Uncertainty Quantification (UQ26). March 2026, talk and organize sessions at INFORMS Optimization Society Conference. Feb 2026, talk at the "Contextual stochastic optimization" Workshop at Banff International Research Station (BIRS). January 2026, talk at Joint Mathematical Meetings (JMM), Special Session on Recent Trends of Stochastic Methods in Modern Generative AI. December 2025, University of Wisconsin-Madison, SILO Seminar. November 2025, University of Michigan, Statistics seminar. November 2025, invited talk at Workshop on "Optimal transport: Stochastics, projections, and applications”, the Fields Institute for Research in Mathematical Sciences, Toronto, Canada. Sept. 2025, invited talk at Detecting Anomalous Structures in Stream Settings (DASS) Workshop, Lancaster University, UK, 2025. August 2025, Keynote Speaker, KDD Workshop on Mining and Learning from Time Series (MileTS). August 2025, Keynote Speaker, KDD Workshop on Temporal Graph Learning. July 2025, invited talk at International Conference on Continuous Optimization (ICCOPT). June 2025, invited talk at INFORMS APS Workshop, Atlanta, GA. June 2025, invited talk at Summer Workshop in AI Science and Engineering at Lingnan University of Hong Kong. June 2025, invited talk at Workshop on Statistical Network Analysis and Beyond (SNAB 2025), Tokyo, Japan. May 2025, invited talk at 7th Conference on Discrete Optimization and Machine Learning, Kyoto, Japan. May 2025, invited talk at Artificial Intelligence Modeling, Analysis, and Control of Complex Systems (AIMACCS) Workshop, Columbus, OH. April 2025, seminar at Duke University, Fuqua School of Business, Decision Sciences Group seminar. April 2025, seminar at University of Houston, Department of Industrial and Systems Engineering. March 2025, seminar at Boston University, Department of Mathematics & Statistic. March 2025, talk at One World Mathematics of INformation, Data, and Signals (1W-MINDS) Seminar. Feb. 2025, seminar at University of Pittsburgh, Industrial Engineering, February 2025. Dec. 2024, seminar at University of Chicago, Booth School of Business, Econometrics and Statistics Colloquium. Dec. 2024, invited speaker at Audio Imagination: NeurIPS 2024 Workshop on AI-Driven Speech, Music, and Sound Generation. Nov. 2024, seminar at Purdue University, Daniels School of Business. Nov. 2024, NSF Workshop on Data-driven Modeling and Prediction of Rare and Extreme Events, one of organizers. Oct. 2024, keynote talk at 1st ACM SIGSPATIAL International Workshop on Spatiotemporal Causal Analysis (STCausal Workshop 2024). Oct. 2024, Program Committee Co-Chair, Generative AI Summit at Georgia Tech, October 24, 2024. Oct. 2024, keynote talk at the 19th INFORMS Workshop on Data Mining and Decision Analytics. Oct. 2024, seminar at Columbia University, Statistics Department. Sept. 2024, seminar at the University of Southern California, Epstein Dept. of Industrial & Systems Engineering. July 2024, give a tutorial at ISIT 2024, in Athens, Greece, on "Theory and methods for deep generative models", with Xiuyuan Cheng (Duke), Taiji Suzuki (University of Tokyo). June 2024, talk at Mostly OM 2024 Workshop, at Tsinghua University. May 2024, Plenary Speaker at the 8th International Workshop in Sequential Methodologies (IWSM) 2024. May 2024, talk at "Statistical machine learning for high dimensional data" at IMS at National University of Singapore. May 2024, participate the “DDSS Frontiers in Data Science Symposium” at Princeton University. April 2024, CORMSIS (Centre for Operational Research, Management Sciences and Information Systems) Seminar, University of Southampton. April 2024, give a tutorial at ICASSP 2024, in Seoul, Korea, on "Deep generative model for inference" with Xiuyuan Cheng (Duke). April 2024, talk at "Women in Optimal Transport" workshop, University of British Columbia. March 2024, invited participant of BIRS Workshop: Optimal Transport and Distributional Robustness. March 2024, organize sessions "Advances in sequential analysis and change-point detection" and "Theory and methods for robust learning" for CISS, held at Princeton University. Feb. 2024, INFORMS Data Mining Webinar on "Generative models for statistical inference". Feb. 2024, Distinguished Lecture Series at ORFE, Princeton University. Feb. 2024, LIONS Seminar at Arizona State University. January 2024, talk at the Statistics Empowering Data Science (SEEDS) Conference at University of Southern California. Dec. 2023, talk at ICSDS 2023 Conference, in Lisbon, Portugal. Dec. 2023, invited participant to NSF Workshop: The Convergence of Smart Sensing Systems, Applications, Analytic and Decision Making. Nov. 2023, talk at Symposium on Theoretical Statistics, Applied Statistics and Probability in Celebration of Tze Leung Lai held by Stanford University. Nov. 2023, give a seminar at Northwestern University IEMS. Nov. 2023, talk at Gwinnett School of Mathematics, Science, and Technology, Lawrenceville, GA, about AI and their applications, to high school students. Nov. 2023, participate NSF Workshop on Self-Driving Laboratories. Nov. 2023, serve on a panel at Emory AI Health Symposium. Nov. 2023, give a statistics seminar at NYU Stern School of Business. Nov. 2023, Applied Probability and Statistics Seminar at the Department of Mathematics and Statistics, Hunter College, CUNY. Oct. 2023, serve on Panel "Foundational Topics in AI" at SAIL. Oct. 2023, serve on Panel "Starting academic career for new and prospective QSR faculty". Oct. 2023, talk at INFORMS on "Variable selection for kernel two-sample tests", and organize a Community Committee Choice Session "Districting for Modern Service Systems" with Woody Zhu. Oct. 2023, talk at NSF AMPS Workshop. Sept. 2023, talk at Allerton Conference, UIUC. August 2023, Invited talk at ICIAM Minisymposium on Optimization, Tokyo, Japan. August 2023, Program Committee for IJCAI 2023 Workshop AI4TS: AI for time series analysis: Theory, Algorithms, and Applications. July 2023, Invited talk at 64th International Statistical Institute (ISI) World Statistics Congress (WSC) 2023, in Session "On statistical learning through the lens of machine learning", Ottawa, Canada. July 2023, Invited talk at ICSA International Conference, at invited session "Recent progresses on change-point analysis", Hong Kong, China. July 2023, Present at NSF/NSTC CAREER Panel at ISIT 2023, in Taipei, to explain the impact of NSF CAREER Award to young researchers and students. June 2023, Invited talk, International Workshop on Applied Probability (IWAP), Thessaloniki, Greece. June 2023, Statistics Seminar at London School of Economics, UK. May 2023, Invited talk at Workshop on Change Point Analysis at the University of Warwick, UK. May 2023, Invited talk at the 7th London Symposium on Information Theory (LSIT), in Session "Mathematics of Machine Learning", London, UK. May 2023, Invited participant of BIRS-IMAG scientific program, on "Modern Statistical and Machine Learning Approaches for High-Dimensional Compound Spatial Extremes", Granada, Spain. May 2023, Invited to participate Statistical Foundations of Data Science and their Applications at Princeton University. May 2023, Invited talk at 8th Workshop on Biostatistics and Bioinformatics, Atlanta, GA. April 2023, Seminar at Northwestern University, Department of Statistics and Data Science. April 2023, Talk at National Institute of Statistical Sciences (NISS) Webinar on "Conformal Inference: Advancing the Boundaries of Machine Learning". April 2023, Seminar at Zuse Institute Berlin (ZIB). March 2023, Seminar at IMSE, Iowa State University. Feb. 2023, Invited talk at ITA workshop. January 2023, Invited talk, Information Theory and Data Science Workshop held at the Institute for Mathematical Science (IMS), National University of Singapore (NUS). Oct. 2022, Featured Speaker at Georgia Statistics Day. Oct. 2022, ISE Seminar at North Carolina State. Oct. 2022, Organize two INFORMS Sessions on "Analytics for Policing and Urban Public Service Operations," with He Wang. Oct. 2022, talk at the Zhejiang University International Workshop on Intelligent Signal Processing. Sept. 2022, talk at a mini-symposium on "Geometric distances and robust data analysis" at the SIAM Data Science conference in San Diego. Aug. 2022, selected to be an ISyE DEI Fellow. August 2022, talk at JSM, in "The Best of AOAS" Session and "Statistical Advances in Learning Large-scale Networks from Massive Data Sets." August 2022, give a lecture at the IEEE East Asian School of Information Theory 2022 (EASIT) in Summer 2022. Report here. August 2022, invited talk at IFDS Workshop on Distributional Robustness in Data Science, at University of Washington. July 2022, invited talk at the ICML Workshop on Distribution-Free Uncertainty Quantification. June 2022, gave a research talk to train faculty participants of Clark Atlanta University, a Historically Black Colleges and University (HBCU). June 2022, taught a session to ISyE Mission Possible, a summer camp for high school students. June 2022, start serving as Associate Editor for IEEE Transactions on Information Theory, in the area of Statistics and Machine Learning. May 2022, I will give a talk in an invited session at the 2022 Statistical Methods in Imaging (SMI) conference, in the session "New statistical and machine learning methods for complex imaging data." May 2022, talk at ITA workshop held by UCSD. May 2022, talk at the NSF ATD Workshop and the NSF AMPS Workshop at George Mason University. May 2022, talk at Conference in Honor of David Siegmund's Contribution to Statistical Sciences at Stanford University. April 2022, Congratulations Woody Zhu for defending his Ph.D. thesis! He will join CMU Heinz School of Public Policy as a tenure-track Assistant Professor. March 10, 2022, I give a keynote talk at Graduate Student Workshop at DIMACS, a NSF Tripod Center at Rutgers University. March 9, 2022, organize special session at CISS (virtual) on "Recent advances in sequential analysis and hypothesis test". March 2, 2022, speak at "Online seminar on spatial and spatio-temporal point processes". I am excited to receive a new NSF grant as PI, in the SCALE MoDL Program "Bridging statistical hypothesis tests and deep learning for reliability and computational efficiency,'' 01/2022-12/2024. I look forward to participating the newly annouced NSF AI Institute for Advances in Optimization. Our paper "Data-driven optimization for police zone design" (jointly with Woody Zhu and He Wang) was selected as a Finalist of the INFORMS Wagner Prize 2021. At INFORMS 2021, I am organizing a Committee Choice Session "Analytics for policing and urban public service operations" (jointly with He Wang), and "Modern algorithms for threat detection." Nov. 2021, talk at Monie A. Ferst Award Symposium, in honor of Professor Jeff Wu. Nov. 2021, I will talk at Cornell ORIE Colloquium. I serve as an Area Chair for NeurIPS 2021. September 2021, give a tutorial entitled "Learning point process networks using discrete events data" at the Graduate International Workshop on Intelligent Signal Processing, organized by Zhejiang University. Aug 2021, talk at IFDS-MADLab Workshop. July 2021, give a short course on "Introduction to Machine Learning and Statistical Modeling" to Center for Disease Control (CDC), Statistical Advisory Group. July 2021, talk at Bernoulli-IMS 10th World Congress in Probability and Statistics. July 2021, talk at Online Seminar on Mathematical Foundations of Data Science. Feb. 2021, virtual ECE seminar at University of California, Davis. Feb. 2021, virtual SILO seminar at University of Wisconsin Madison. Dec. 2020, virtual statistics seminar at University of Pennsylvania, Wharton School. Nov. 2020, virtual seminar at CMU, Tepper School of Business. Nov. 2020, "Woody" Shixiang Zhu won the Second Place in the Best Paper Competititon for the 15th INFORMS Workshop on Data Mining and Decision Analytics for paper entitled "Sequential Adversarial Anomaly Detection for Dependent Events". Congratulations! Nov. 2020, co-found and co-organized the new Machine Learning/AI Cluster at 2020 INFORMS meeting. Nov. 2020, virtual seminar at University of South Florida. Oct. 2020, Liyan Xie and Henry Yuchi received the Georgia Tech IDEaS-TRIAD Research Scholarship, for their projects "Distributionally Robust Statistical Tests and Learning" and “Diffusion-based Gaussian Process Dynamic Model for Material Degradation and Prognostic Analysis”. Congratulations! Oct. 2020, co-organizing a Special Issue at IEEE Journal on Selected Areas in Information Theory, on "Sequential, active, and reinforcement learning". Please see here for call-for-paper. Oct. 2020, Liyan Xie was selected to participate the "Rising Stars 2020" Workshop. Congratulations! Oct. 2020, virtual statistics seminar at Duke University. July 2020, virtual seminar at CDC on "High-resolution spatio-temporal covariates models for county-level COVID-19 data in the US". July 2020, Alexander Bukharin received the President’s Undergraduate Research Salary Award (PURA) for working on our project: COVID-19 spatial-temporal sequential modeling and prediction. June 2020, I was selected to join the 2020-2021 Cohort of the Office of Provost's Emerging Leaders Program. May 2020, give virtual statistics seminar at Rutgers University. April 2020, Alexander Bukharin received the GT COE Outstanding Undergraduate Research Award for his work with us on Atlanta police districting. March 2020, I organized a session on "Recent Advances in Sequential Analysis" at CISS, Princeton (canceled due to COVID-19). I will serve as an Associate Editor for Sequential Analysis, 2020-2022. Jan. 2020, our group has 3 papers accepted by IEEE ICASSP 2020: "Adversarial anomaly detection for marked spatio-temporal streaming data", "Online community detection by spectral CUSUM", and "Sequential vessel trajectory identification using truncated Viterbi algorithm." |
