H. Milton Stewart School of Industrial and
Georgia Institute of Technology
Phone: (404) 894-2334
Email: ymei AT isye.gatech.edu
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. K. Liu, R. Zhang and Y. Mei. Scalable
SUM-Shrinkage schemes for distributed monitoring large-scale data streams,
Zhang, J. Wang, and Y. Mei. Classification
of paper citation trajectories through functional Poisson regression model,
Holte and Y.
in the specification of ordinary differential equations and parameter
estimation in modelling biological processes, 2016.
4. Y. Li and Y. Mei. D-ary sequential tests of circular error probability,
1. S.E. Holte, E. Lee
and Y. Mei. Symmetric
directional false discovery rate control, Accepted by Statistical
2. K. Liu and Y. Mei. Discussion
on “Sequential detection/isolation of abrupt changes’ by Igor Nikiforov, Sequential Analysis, 2016.
- 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.
- Yuan Wang and Y. Mei. Large-Scale
multi-stream quickest change detection via shrinkage post-change
Transactions on Information Theory, vol. 61, page 6926-6938, 2015.
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.
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.
Wang, Y. Mei and D. Hicks. Comments
on “Quantifying long-term scientific impact”. Science, vol. 345 no. 6193, page 149, 2014.
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,
Wang and Y. Mei. A
multistage procedure for decentralized sequential multi-hypothesis testing
problems. Sequential Analysis,
vol. 31, pp. 505-527, 2012.
- Y. Wang and Y. Mei. Asymptotic
optimality theories for decentralized multi-hypothesis sequential
Transactions on Information Theory, vol. 57, issue 10, page 7068-7083,
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.
- Y. Mei. Efficient
scalable schemes for monitoring a large number of data streams. Biometrika,
vol. 97, page 419-433, 2010.
- Y. Mei, “Is average
run length to false alarm always an informative criterion?” (with
discussions), Sequential Analysis,
vol. 27, page 354-419, 2008.
- 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,
- Y. Mei, L. Wang, and S. E. Holte.
comparison of methods for determining HIV viral set point.” Statistics in Medicine, vol. 27,
issue 1, page 121-139, 2008.
- 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.
- 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.
- 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.
- Y. Mei, Information
bounds and quickest change detection in decentralized decision systems.
Transactions on Information Theory, vol. 51, issue 7, page 2669-2681, 2005.
- Y. Mei, Asymptotically
optimal methods for sequential change-point detection. Ph.D. thesis, 2003.
Course(s) I am teaching this semester