Yaakov Malinovsky

Associate Professor

Department of Mathematics and Statistics
University of Maryland, Baltimore County
1000 Hilltop Circle
Baltimore, MD 21250

Office: MP 421
Voice: (410) 455-2968

E-mail: yaakovm@umbc.edu

CURRICULUM VITAE

Education

Ph.D. in Statistics, Department of Statistics, The Hebrew University of Jerusalem, Israel, 2009

Research Interests

Decision theory, Stochastic ordering, Sequential selection, Sequential methods, Group testing, and Nonparametric methods.

Erdös Number 2

Editorial Service

Associate Editor, Methodology and Computing in Applied Probability, May 2023- Present

Associate Editor, The American Statistician, August 2017- Present

Associate Editor, Journal of Applied Statistics, February 2017- March 2019

Research Funding

United States - Israel Binational Science Foundation (BSF):

Grant #2020063 "Minimax online learning policies in stochastic sequential selection and assignment,'' [with A. Goldenshluger, Haifa University and A. Zeevi, Columbia University] 10/2021-10/2025

Publications

Journal Articles

Malinovsky, Y. and Rinott, Y. On stochastic orders of absolute value of order statistics in symmetric distributions. Statistics and Probability Letters, 79, 2086-2091, 2009. link
Malinovsky, Y. and Rinott, Y. Prediction of ordered random effects in a simple small area model. Statistica Sinica, 20, 697-714, 2010. link
Malinovsky, Y. and Rinott, Y. Best invariant and minimax estimation of quantiles in finite populations. Journal of Statistical Planning and Inference, 141(8), 2633-2644, 2011. link
Vexler, A., Tsai W., and Malinovsky Y. Estimation and testing based on data subject to measurement errors: from parametric to non-parametric likelihood methods.. Statistics in Medicine, 31, 2498-2512, 2012. link
Malinovsky, Y., Albert, P.S., and Schisterman, E.F. Pooling designs for outcomes under a Gaussian random effects model. Biometrics, 68, 45-52, 2012. link
Malinovsky, Y., and Kogan, J. Monitoring Threshold Functions over Distributed Data Streams with Node Dependent Constraints. Algorithms, 5, 379-397, 2012. link
Kagan, A.M., and Malinovsky, Y. Monotonicity in the Sample Size of the Length of Classical Confidence Intervals. Statistics and Probability Letters, 83, 78-82, 2013. link
Kagan, A.M., and Malinovsky, Y. On the Nile Problem by Sir Ronald Fisher. Electronic Journal of Statistics, 7, 1968-1982, 2013. link
Kagan, A.M., Malinovsky, Y., and Mattner, L. Partially Complete Sufficient Statistics are Jointly Complete. Theory of Probability and Its Applications, 59, 542-561, 2014. link
Malinovsky, Y., and Albert, P.S. A note on the minimax solution for the two-stage group testing problem. The American Statistician, 69, 45-52, 2015. link
Guha, N., Roy, A., Malinovsky, Y., Datta, G. An Optimal Shrinkage Factor in Prediction of Ordered Random Effects . Statistica Sinica, 26, 1709-1728, 2016. link
Malinovsky, Y., Albert, P.S., and Roy, A. Reader reaction: A note on the evaluation of group testing algorithms in the presence of misclassification. Biometrics, 72, 299-302, 2016. link
Kagan, A.M., and Malinovsky, Y. On the structure of UMVUEs . Sankhya A, 78, 124-132, 2016. link
Haber, G., Malinovsky, Y. Random walk designs for selecting pool sizes in group testing estimation with small samples. Biometrical Journal, 59, 1382-1398, 2017. link
Haber, G., Malinovsky, Y., and Albert, P.S. Sequential estimation in the group testing problem. Sequential Analysis, 37, 1-17, 2018. link
Malinovsky, Y., and Zacks, S. Proportional closeness estimation of probability of contamination under group testing . Sequential Analysis, 37, 145-157, 2018. link
Malinovsky, Y. On optimal policy in the group testing with incomplete identification. Statistics and Probability Letters, 140, 44-47, 2018. link
Fay, M., and Malinovsky, Y. Confidence Intervals on the Mann-Whitney parameter that give unified inferences with the Wilcoxon-Mann-Whitney test . Statistics in Medicine, 37, 3991-4006, 2018. link
Malinovsky, Y., and Albert, P.S. Revisiting nested group testing procedures: new results, comparisons, and robustness. The American Statistician, 73, 117-125, 2019. link
Haber, G., Malinovsky, Y. Efficient methods for the estimation of the multinomial parameter for the two-trait group testing model. Electronic Journal of Statistics, 13, 2624-2657, 2019. link
Malinovsky, Y. Sterrett procedure for the generalized group testing problem. Methodology and Computing in Applied Probability, 21, 829-840, 2019. link link
Haber, G., Malinovsky, Y. On the construction of unbiased estimators for the group testing problem. Sankhya A, 82, 220-241, 2020. link link
Malinovsky, Y., Haber, G., Albert, P. An optimal design for hierarchical generalized group testing. JRSS C, 2020. link link
Goldenshluger, A., Malinovsky, Y., and Zeevi, A. A unified approach for solving sequential selection problems. Probability Surveys, 17, 214-256, 2020. link
Malinovsky, Y. Conjectures on Optimal Nested Generalized Group Testing Algorithm. Applied Stochastic Models in Business and Industry, 36, 1029-1036, 2020. link link
De Santis, E., Malinovsky, Y., and Spizzichino, F. Stochastic precedence and minima among dependent variables. Methodology and Computing in Applied Probability 23, 187--205, 2021. link link
Haber, G., Malinovsky, Y., Albert, P. Is Group Testing Ready for Prime-time in Disease Identification?. Statistics in Medicine, Discussion Article, 40, 3865-3880, 2021. link link link link link link
Mehta, T., Malinovsky, Y., Abnet, C., Albert, P. Using Group Testing in a Two-Phase Epidemiologic Design to Identify the Effects of a Large Number of Antibody Reactions on Disease Risk. BMC Medical Research Methodology 22 (1), 1-9, 2022. link
Malinovsky, Y., and Zacks, S. Two-Stage and Sequential Unbiased Estimation of N in Binomial Trials, when the Probability of Success p is Unknown. Sequential Analysis, 41, 275-284, 2022. link link
Malinovsky, Y. A Short Probabilistic Proof of a Binomial Identity. The College Mathematics Journal, 53, 394-395, 2022 link
Malinovsky, Y. A note on the closed-form solution for the longest head run problem of Abraham de Moivre. The Mathematical Intelligencer, 44, 267-268, 2022. link link
Malinovsky, Y., Moon, J. W. On the negative dependence inequalities and maximal score in round-robin tournament. Statistics and Probability Letters, 185, 109432, 2022. link link
Malinovsky, Y. On the distribution of winners' scores in a round-robin tournament. Probability in the Engineering and Informational Sciences, 36, 1098-1102, 2022. link link
Best, A., Malinovsky, Y., Albert, P. The efficient design of nested group testing algorithms for disease identification in clustered data. Journal of Applied Statistics, 50, 2228-2245, 2023. link
Malinovsky, Y., Rinott, Y. On Tournaments and Negative Dependence. Journal of Applied Probability, 60, 945-954, 2023. link link
Alon, N., Malinovsky, Y. Hitting a prime in 2.43 dice rolls (on average) . The American Statistician, 77, 301-303, 2023. link link
Malinovsky, Y., Moon, J. W. On round-robin tournaments with a unique maximum score.. Australasian Journal of Combinatorics, 89(1), 24-31, 2024. link link

Miscellania

Malinovsky, Y. Follow Up on Detecting Deficiencies: An Optimal Group Testing. End Notes: Mathematics Magazine 92, 398, 2019. link link
Malinovsky, Y. Book Review. Biometrics, 2019. link
Malinovsky, Y. Layman's abstract for paper on conjectures on optimal nested generalized group testing algorithm. Statistics Views, Willey, 2020. link
Malinovsky, Y., Albert, P. Nested Group Testing Procedures for Screening. Wiley StatsRef-Statistics Reference Online, Accepted, 2021. link

Preprints

Malinovsky, Y. A note on the distribution of the extreme degrees of a random graph via the Stein-Chen method. Submitted for publication. link
Malinovsky, Y., Sonin, I. Water Puzzle and Marginal Utility Optimization.. Submitted for publication. link
Goldenshluger, A., Malinovsky, Y., and Zeevi, A. Optimal single threshold stopping rules and sharp prophet inequalities. Submitted for publication. link

Teaching

Stat 355 Introduction to Probability and Statistics for Scientists and Engineers (Spring 2012, Spring 2016, Spring 2017, Fall 2017, Spring 2018, Spring 2019, Fall 2020, Spring 2022, Fall 2022, Spring 2023 )
Stat 405 Survey Sampling (Spring 2014)
Stat 417 Introduction to Time Series Data Analysis (Fall 2011)
Stat 451 Introduction to Probability Theory (Spring 2023, Spring 2024)
Stat 455 Design of Experiments and Quality Controls (Fall 2014)
Stat 490 Special Topics in Statistics: Stochastic Processes (Fall 2013)
Stat 490 Special Topics in Statistics: Nonparametric Methods (Fall 2015, Fall 2017, Spring 2020)
Stat 490 Special Topics in Statistics: Probability Models with Applications (Fall 2016, Spring 2019, Fall 2021)
Stat 490 Special Topics in Statistics: Decision Theory with Applications (Fall 2019, Spring 2022)
Stat 490 Special Topics in Statistics: Topics in Probability (Fall 2023)
Stat 616 Nonparametric Statistics (Spring 2015, Fall 2016, Spring 2018, Fall 2021, Fall 2022 )
Stat 651 Probability (Fall 2012, Fall 2013, Fall 2014, Fall 2015, Fall 2018, Fall 2020, Fall 2023 )
Stat 653 Mathematical Statistics (Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2020, Spring 2021, Spring 2024)
Stat 710 Topics on Mathematical Statistics and Statistical Inference (Spring 2013)
Stat 710 Topics on Group Testing and Sequential Methods (Spring 2017)
Stat 700 Topics on Sequential Selection and Group Testing (Spring 2021)