Department of Mathematics and Statistics
- Dr. Michael Baron is Professor at the Department of Mathematics and Statistics. He came to AU in 2014, after 19 years at the University of Texas at Dallas. Supported by grants from the National Science Foundation, the National Security Agency, the Actuarial Foundation, and the Semiconductor Technical Council, he conducts research in the areas of sequential analysis, change-point detection, and Bayesian inference, applying obtained results in epidemiology, clinical trials, cyber security, energy finance, and semiconductor manufacturing. The last application brought M. Baron to IBM T. J. Watson Research Center, where he was a one-year Academic Visitor in 2003-04. M. Baron has published three books, a number of research articles and book chapters, and gave an even greater number of invited presentations and seminars. In 2007 M. Baron received Abraham Wald prize for the best paper in sequential analysis, and in 2013 he was elected a Fellow of the American Statistical Association. Currently, he serves as Associate Editor of the Journal of Sequential Analysis. He is a member of the American Statistical Association and the International Society for Bayesian Analysis. M. Baron has a University Diploma in Mathematics from St. Petersburg State University, Russia (1992), and a PhD degree in Statistics from the University of Maryland (1995). His University Diploma paper entitled "On the First Passage Time for Queueing Processes" was supervised by Prof. Ildar Ibragimov, and his doctoral dissertation "Confidence Estimation in the Change-Point Problem" was supervised by Prof. Andrew Rukhin. In his turn, M. Baron graduated nine doctoral students and is currently working on three more. During his free time, he travels and plays piano, Go, bridge, and ice hockey.
DegreesPhD, Maryland Baltimore County, Statistics, 1995
MS, State University of St. Petersburg (Russia), Mathematics, 1992.
Languages Spoken:English, Russian, ... and SAS
Scholarly, Creative & Professional Activities
Probability and Statistics for Computer Scientists, by Michael Baron (426 pp.) Chapman & Hall / CRC, Boca Raton, FL, 2007. ISBN 1584886412.
Its 2nd edition (473 pp.). Chapman & Hall / CRC, Boca Raton, FL, 2013. ISBN 1439875901.
Bourdieu’s Demon. Volume 1: Strategies of the Upper Middle Class in the Information Age, by Richard Baker and Michael Baron (292 pp.) CreateSpace Publishing, North Charleston, SC, 2012. ISBN 147826974X.
M. Baron. Asymptotically Pointwise Optimal Change Detection in Multiple Channels, Sequential Analysis: forthcoming, 2014.
X. Yu, M. Baron, and P. Choudhary. Change-Point Detection in Binomial Thinning Processes, with Applications in Epidemiology, Sequential Analysis 32 (3), 350-367, 2013.
S. De and M.Baron. Step-up and step-down methods for testing multiple hypotheses in sequential experiments, J. of Stat. Planning and Inference 142: 2059-2070, 2012.
S. Suzuki and M.Baron. Construction of the optimal sequential plan for testing a treatment for an adverse effect, Sequential Analysis 30 (3): 261-279, 2011.
M. Baron, A. Takken, E. Yashchin, and M. Lanzerotti. Modeling and Forecasting of Defect-Limited Yield in Semiconductor Manufacturing. IEEE Transactions on Semiconductor Manufacturing, 21(4), 614-624, 2008.
C. Schmegner and M.Baron. Sequential Plans and Risk Evaluation. Sequential Analysis, 26(4), 335--354, 2007.
C. Schmegner and M.Baron. Principles of optimal sequential planning. Sequential Analysis, 23(1), 11--32, 2004.
M.Baron. Bayes stopping rules in a change-point model with a random hazard rate. Sequential Analysis, 20 (3), 147-163, 2001.
M.Baron, C. K. Lakshminarayan, and Z. Chen. Markov random fields in pattern recognition for semiconductor manufacturing. Technometrics, 43 (1), 66-72, 2001.
M.Baron. Nonparametric adaptive change-point estimation and on-line detection. Sequential Analysis, 19 (12), 1-23, 2000.
M.Baron. On statistical inference under asymmetric loss functions. Statistics & Decisions, 18 (4), 367-388, 2000.
Grants and Sponsored Research
Project: Sequential testing of multiple hypotheses, simultaneous confidence intervals, and multichannel change-point detection (sole PI). Sponsor: National Science Foundation, Division of Mathematical Sciences (2010-2014)
- Sequential analysis and optimal sequential designs
- Change-point estimation and on-line detection
- Multiple comparisons
- Bayesian Inference
- Application of statistics in epidemiology, clinical trials, semiconductor manufacturing, actuarial science, energy finance, and cyber security
Honors, Awards, and Fellowships
- Fellow of the American Statistical Association (2013)“For outstanding contributions to the theory and applications of sequential analysis and change-point problems, excellence in teaching and mentoring of doctoral students, dissemination of statistical knowledge via book authorship, and promotion of statistical research in diverse areas of industry.”
- Regents’ Outstanding Teaching Award (2014)
- Abraham Wald Prize for the best paper in the Journal of Sequential Analysis (2007)
- Associate Editor of Sequential Analysis
- Invited Technometrics paper of 2001
Grants and Sponsored Research
- Project: Statistical methods for gaining precision in credibility estimation (PI). Sponsor: Actuarial Foundation, Individual Grants Competition.
- Project: ATD: Efficient online detection based on multiple sensors, with applications to cybersecurity and discovery of biological threats (PI). Sponsor: National Science Foundation, Mathematical Sciences