Yao Xie 谢瑶

yao photo

Yao Xie (Official webpage) (CV)(Research Statement)
Coca-Cola Foundation Chair and Professor
H. Milton Stewart School of Industrial and Systems Engineering (ISyE)
Associate Director, Machine Learning Center
Adjunct Professor, School of Electrical and Computer Engineering (ECE)
Georgia Institute of Technology


Office Phone: (404) 385-1687
Office: Groseclose 445
765 Ferst Dr NW, Atlanta, GA, 30332-0205
Email: Email address

Research Interests

My research lies at the intersection of statistics, optimization, and machine learning. I work on developing computationally efficient and statistically powerful algorithms with guarantees, for engineering problems arising from various real-world applications.

I am particularly interested in sequential data analysis and change-point detection, and their applications in sensor networks, social networks, imaging and communications.

For recent publications and preprints, please see here. My Erdős number is 3.

My work has generated societal and policy impact: see here for our work on data-driven policing.

Articles by GT about my research "In pursuit of better data forecasting." and "Driving data science innovation as Coca-Cola Foundation Chair."

I am humbled and honored to receive the prestigious INFORMS Donald P. Gaver, Jr. Early Career Award for Excellence in Operations Research in 2022, which is awarded to one recipient across INFORMS annually. Citation: "For outstanding research contributions at the interface of operations research, statistics, machine learning and optimization; for successfully applying her research talent to applications of societal importance; and for contributions to the education and mentoring of students at all levels." Here is my acceptance speech and picture at INFORMS Award Ceremony, Oct. 2022 with (a subset) of my (current and former) students.

Currently Teaching

Undergraduate course: ISyE 4803, Foundations and Applications of Machine Learning. Fall 2023.

Graduate course: ISyE/OMSA 6740, Computational Data Analysis. Fall 2023.


Area Chair, ICLR 2024.

I will give an ICASSP 2024 Tutorial (with Xiuyuan Cheng at Duke) on "Deep generative model for inference."

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.

January 2024, talk at 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."