• Probability and Statistics for Computer Scientists, by Michael Baron. Third edition (486 pp.) Chapman & Hall / CRC, Boca Raton, FL, 2019. ISBN 9781138044487.
• Probability and Statistics for Computer Scientists, by Michael Baron. Second edition (473 pp.) Chapman & Hall / CRC, Boca Raton, FL, 2014. ISBN 1439875901.
• Probability and Statistics for Computer Scientists, by Michael Baron (426 pp.) Chapman & Hall / CRC, Boca Raton, FL, 2007. ISBN 1584886412.
• 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.
Refereed journal articles and book chapters
• M. Baron. On the first passage time for waiting processes. Theory of Probab. and Appl., 41: 328-334, 1996.
• M. Baron and A. L. Rukhin. Asymptotic behavior of confidence regions in the change-point problem. J. of Stat. Planning and Inference, 58:263-282, 1997.
• M. Baron. Convergence rates of change-point estimators and tail probabilities of the first-passage-time process. Canadian J. of Statistics, 27:183-197, 1999.
• M. Baron and A. L. Rukhin. Distribution of the number of visits of a random walk. Stochastic Models, 15: 593-597, 1999.
• 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.
• 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 and A. L. Rukhin. Perpetuities and asymptotic change-point analysis. Statistics and Probability Letters, 55 (1), 29-38, 2001.
• M. Baron. Bayes stopping rules in a change-point model with a random hazard rate. Sequential Analysis, 20 (3), 147-163, 2001.
• M. Baron, M. Rosenberg, and N. Sidorenko. Electricity pricing: modeling and prediction with automatic spike detection. Energy, Power, and Risk Management, 36-39, October 2001.
• M. Baron, M. Rosenberg, and N. Sidorenko. Divide and conquer: forecasting power via automatic price regime separation. Energy, Power, and Risk Management, 70-73, March 2002.
• N. Sidorenko, M. Baron, and M. Rosenberg. Estimating oil price volatility: a GARCH model. Energy, Power, and Risk Management, 62-65, October 2002.
• M. Baron. Bayes and asymptotically pointwise optimal stopping rules for the detection of influenza epidemics. In C. Gatsonis, R. E. Kass, A. Carriquiry, A. Gelman, D. Higdon, D. K. Pauler and I. Verdinelli, Eds., Case Studies in Bayesian Statistics, vol. 6, pages 153-163, Springer-Verlag, New York, 2002.
• M. Rosenberg, J. D. Bryngelson, N. Sidorenko; M. Baron. Price spikes and real options: transmission valuation. In E. I. Ronn, ed., Real Options and Energy Management, pages 323-370, Risk Books, London, 2002.
• M. Rosenberg, J. D. Bryngelson; M. Baron. Probability and stochastic calculus: review of probability concepts. In E. I. Ronn, ed., Real Options and Energy Management, pages 659-697, Risk Books, London, 2002.
• M. Baron and N. Granott. Consistent estimation of early and frequent change points. In J. Haitovsky, H. R. Lerche, and Y. Ritov, eds., Foundations of Statistical Inference, pages 181-194, Physica-Verlag, Heidelberg, New York, 2003.
• M. Baron. Sequential methods for multistate processes. In N. Mukhopadhyay, S. Datta, S. Chattopadhyay, eds., Applications of Sequential Methodologies, 55-73, Marcel Dekker, Inc., New York, 2004.
• M. Baron. Detection of epidemics as a sequential change-point problem. In V. Antonov, C. Huber, M. Nikulin, V. Polischook, eds.; Longevity, Aging and Degradation Models in Reliability, Public Health, Medicine and Biology, volume 2, pages 31-43, St. Petersburg, 2004.
• R. Gill and M. Baron. Consistent estimation in generalized broken-line regression. J. of Stat. Planning and Inference, 126(2), 441-460, 2004.
• C. Schmegner and M. Baron. Principles of optimal sequential planning. Sequential Analysis, 23(1), 11-32, 2004.
• M. Baron and A. Tartakovsky. Asymptotic optimality of change-point detection schemes in general continuous-time models. Sequential Analysis, 25(3) 257-296, 2006.
• R. Gill, J. Keating, and M. Baron. Detecting abrupt leaks in blended underground storage tanks. Communication is Statistics: Theory and Methods, 35(4) 727-742, 2006.
• C. Schmegner and M. Baron. Sequential Plans and Risk Evaluation. Sequential Analysis, 26(4), 335-354, 2007.
• H. C. Urschel, L. L. Hanselka, I. Gromov, L. White, and M. Baron. Open-Label Study of a Proprietary Treatment Program Targeting Type A γ-Aminobutyric Acid Receptor Dysregulation in Methamphetamine Dependence. Mayo Clinic Proceedings, 82(10), 1170-1178, 2007.
• J. W. Cangussu and M. Baron. Automatic Identification of Change Points for the System Testing Process. COMPSAC (1), 377-384, 2007.
• 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.
• S. Suzuki and M. Baron. ε-Bayes Sequential Plans. Advances and Applications in Statistics 11 (2), 173-183, 2009.
• M. Rosenberg, J. D. Bryngelson, M. Baron, and A. D. Papalexopoulos. Transmission Valuation Analysis Based on Real Options with Price Spikes," in Handbook of Power Systems II, series Energy Systems, S. Rebennack, P.M. Pardalos, M.V.F. Pereira and N. Iliadis (eds). Springer, 2010, pp. 101-125
• M. Baron and S. Efromovich. Discussion on "Quickest Detection Problems: Fifty Years Later" by Albert N. Shiryaev, Sequential Analysis, 29: 398-403, 2010.
• J. W. Cangussu, S. W. Haider, K. Cooper, and M. Baron. On the selection of software defect estimation techniques. Software Testing, Verification and Reliability 21 (2), 125-152, 2011.
• H. C. Urschel, L. L. Hanselka, and M. Baron. A controlled trial of flumazenil and gabapentin for initial treatment of methylamphetamine dependence. J. of Psychopharmacology 25 (2), 254-262, 2011.
• 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.
• S. De and M. Baron. Sequential Bonferroni methods for multiple hypothesis testing with strong control of familywise error rates I and II, Sequential Analysis 31 (2), 238-262, 2012.
• 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.
• X. Yu, M. Baron, and P. Choudhary. Change-Point Detection in Binomial Thinning Processes, with Applications in Epidemiology, Sequential Analysis, 32: 350-367, 2013.
• M. Baron. Discussion on "Change-Points: From Sequential Detection to Biology and Back" by David Siegmund, Sequential Analysis, 32: 15-18, 2013.
• C. K. Lakshminarayan and M. Baron. Pattern recognition in large-scale data sets: application in integrated circuit manufacturing. In V. Bhatnagar and S. Srinivasa, eds., Big Data Analytics, 185-196, Springer, Heidelberg, Germany, 2013.
• X. Chen and M. Baron. Change-point analysis of survival data with application in clinical trials, Open J. of Statistics 4, 663-677, 2014. DOI: 10.4236/ojs.2014.49062.
• M. Baron. Asymptotically pointwise optimal change detection in multiple channels, Sequential Analysis 33 (4), 440-457, 2014.
• A. Haque, S. Chandra, L. Khan, and M. Baron. MapReduce guided approximate inference over graphical models. In 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), 446-453, IEEE, 2014. DOI: 10.1109/CIDM.2014.7008702
• S. De and M. Baron. Sequential tests controlling generalized familywise error rates, Statistical Methodology 23, 88-102, 2015.
• A. Haque, L. Khan, and M. Baron. Semi-supervised adaptive framework for classifying evolving data stream. In T. Cao, E.-P. Lim, Z.-H. Zhou, T.-B. Ho, D. Cheung, and H. Motoda, eds., Advances in Knowledge Discovery and Data Mining, Part II, 55--73, Cham, Switzerland, 2015.
• M. Baron and R. Xu. Sequential testing for full credibility, Variance: accepted.
• A. Haque, L. Khan, and M. Baron. SAND: Semi Supervised Adaptive Novel Class Detection and Classification over Data Stream. 30th AAAI Conference on Artificial Intelligence (AAAI-16): accepted.
• M. Baron and S. Zacks. Discussion on “Sequential detection/isolation of abrupt changes” by Igor V. Nikiforov. Sequential Analysis: accepted.