Description: Yajun Mei                          Yajun Mei

          Associate Professor
            H. Milton Stewart School of Industrial and Systems Engineering
            Georgia Institute of Technology
            Phone: (404) 894-2334
            Fax: 404-894-2301

            Email: ymei AT isye dot gatech dot edu


Mailing Address:

H. Milton Stewart School of Industrial and Systems Engineering
Georgia Institute of Technology
Atlanta, GA 30332-0205


I received a B.S. in Mathematics in 1996 from Peking University, P.R. China, and a Ph.D. in Mathematics with a minor in Electrical Engineering in 2003 from the California Institute of Technology, Pasadena, CA. I have also worked as a Postdoc in Biostatistics for two years in the Fred Hutchinson Cancer Research Center in Seattle, WA. My research interests include change-point problems and sequential analysis in Mathematical Statistics; sensor networks and information theory in Engineering; as well as longitudinal data analysis, random effects models, and clinical trials in Biostatistics. Currently I am interested in high-dimensional streaming data analysis over networks, and their applications in engineering and biomedical sciences. 


1.     C. Zhang,  Y. Mei and F. Tsung. Monitoring Multivariate Data via KNN Learning, Submitted.

2.     K. Liu, and  Y. Mei. Improved Performance Properties of the CISPRT Algorithm for Distributed Sequential Detection, Submitted.

3.     Y. Li and Y. Mei. Efficient Robust Sequential Test of Circular Error Probability via D-ary Quantization, Submitted.  

Selected Publications

1.     Yuan Wang, Y. Mei and K. Paynabar.  Thresholded Multivariate Principal Component Analysis for Phase I Multichannel Profile Monitoring, Technometrics, 2017 (Accepted).

2.     S. Holte and Y. Mei. Precision in the specification of ordinary differential equations and parameter estimation in modelling biological processes, Chapter 12 in the book entitled K26357: Quantitative Methods for HIV/AIDS Research, 1st Edition, 2017 (Accepted).

3.     R. Zhang, J. Wang, and Y. Mei. Search for evergreens in science: a functional data analysis, Journal of Informetrics, 2017 (Accepted).

4.     K. Liu, R. Zhang and Y. Mei. Scalable SUM-Shrinkage schemes for distributed monitoring large-scale data streams, Statistica Sinica, 2017 (Accepted).

5.     S.E. Holte, E. Lee and Y. Mei. Symmetric directional false discovery rate control, Statistical Methodology, vol. 33, page 71-82, 2016.

6.     K. Liu and Y. Mei. Discussion on “Sequential detection/isolation of abrupt changes’ by Igor Nikiforov, Sequential Analysis, vol. 35, page 316-319, 2016.

7.     Y. Li and Y. Mei. Effect of bivariate data’s correlation on sequential tests of circular error probability. Journal of Statistical Planning and Inference, vol. 171, page 99-114, 2016.

8.     Yuan Wang and Y. Mei. Large-Scale multi-stream quickest change detection via shrinkage post-change estimation. IEEE Transactions on Information Theory, vol. 61, page 6926-6938, 2015.

9.     C.D. Fuh and Y. Mei. Quickest change detection and Kullback-Leibler divergence for two-state hidden Markov models. IEEE Transactions on Signal Processing, vol. 63, No. 18, page 4866-4878, 2015.

10.  K. Liu, Y. Mei and J. Shi. An adaptive sampling strategy for online high-dimensional process monitoring. Technometrics, vol. 57, No. 3, page 305-319, 2015. 

11.  J. Wang, Y. Mei and D. Hicks. Comments on “Quantifying long-term scientific impact”. Science, vol. 345 no. 6193, page 149, 2014. 

12.  Y. Wang and Y. Mei. Quantization effect on the log-likelihood ratio and its application to decentralized sequential detection. IEEE Transactions on Signal Processing, vol. 61, issue 6, page 1536-1543, 2013.

13.  Y. Wang and Y. Mei. A multistage procedure for decentralized sequential multi-hypothesis testing problems. Sequential Analysis, vol. 31, pp. 505-527, 2012.

14.  Y. Wang and Y. Mei. Asymptotic optimality theories for decentralized multi-hypothesis sequential detection. IEEE Transactions on Information Theory, vol. 57, issue 10, page 7068-7083, 2011.

15.  Y. Mei, S. W. Han and K. Tsui. Early detection of a change in Poisson rate after accounting for population size effects. Statistica Sinica, vol. 21, page 597-624, 2011.

16.  Y. Mei. Efficient scalable schemes for monitoring a large number of data streams. Biometrika, vol. 97, page 419-433, 2010.

17.  Y. Mei, “Is average run length to false alarm always an informative criterion?” (with discussions), Sequential Analysis, vol. 27, page 354-419, 2008.

18.  Y. Mei, “Asymptotic optimality theory for decentralized sequential hypothesis testing in sensor networks,” IEEE Transactions on Information Theory, vol. 54, issue 5, page 2072-2089, 2008.

19.  Y. Mei, L. Wang, and S. E. Holte. “A comparison of methods for determining HIV viral set point.” Statistics in Medicine, vol. 27, issue 1, page 121-139, 2008.

20.  Y. Mei, Suboptimal properties of Page’s CUSUM and Shiryayev-Roberts procedures in change-point problems with dependent observations. Statistica Sinica, vol. 16, page 883-897, 2006.

21.  Y. Mei, Comments on “A note on optimal detection of a change in distribution” by Benjamin Yakir  The Annals of Statistics, vol. 34, no. 3, page 1570-1576, 2006.

22.  Y. Mei, Sequential change-point detection when unknown parameters are present in the pre-change distribution. The Annals of Statistics, vol. 34, no. 1, page 92-122, 2006.

23.  Y. Mei, Information bounds and quickest change detection in decentralized decision systems. IEEE Transactions on Information Theory, vol. 51, issue 7, page 2669-2681, 2005.

24.  Y. Mei, Asymptotically optimal methods for sequential change-point detection. Ph.D. thesis, 2003.


Course(s) I am teaching this semester

  • Spring 2017: ISyE 7406 (Data Mining and Statistical Learning)