STATISTICS · MACHINE LEARNING · BIOSTATISTICS
Assistant Professor of Statistics · Minnesota State University, Mankato
Statistical methodology, statistical machine learning, predictive modeling, meta-analysis, and collaborative health research.
ABOUT
Dr. Md Monzur Murshed is an Assistant Professor in the Department of Mathematics and Statistics at Minnesota State University, Mankato. His work is rooted in statistical methodology and extends to statistical machine learning, predictive modeling, meta-analysis, survival analysis, and biomedical data science.
His research connects rigorous statistical analysis with meaningful applied problems. Current projects use SEER, PhysioNet, and The Cancer Genome Atlas (TCGA) to study cancer survival, health disparities, clinical outcomes, and interpretable machine learning. Additional projects address research on aging and patient-reported outcomes through the MSU–Mayo Clinic Health System Seed Grant Program.
He is committed to student mentorship. He supervises undergraduate and graduate student researchers, helping them develop statistical reasoning, programming skills, scientific writing, posters, and journal manuscripts.
RESEARCH
Research centers on statistical machine learning, statistical inference, and biomedical data science, with applications to cancer, clinical outcomes, population health, and aging.
Development and application of statistical learning methods for prediction, classification, feature selection, model interpretation, and analysis of complex health data. Current work emphasizes interpretable models, imbalanced outcomes, and rigorous performance evaluation.
Analysis of large biomedical and clinical data resources, including SEER cancer registry data, The Cancer Genome Atlas (TCGA), and PhysioNet. Research focuses on reproducible analysis and questions with clear clinical or public-health relevance.
Survival modeling for cancer prognosis, treatment outcomes, and health disparities. Current projects examine breast, lung, and tonsillar cancers using Cox models, relative survival, competing-risk methods, and population-based data.
Methods for tests and confidence intervals based on information from independent sources. Research includes combined tests for common parameters, univariate calibration, generalized inference, and evaluation of frequentist operating characteristics.
Statistical methods for synthesizing evidence across independent studies and heterogeneous data sources. Areas of interest include effect estimation, percentile-based measures, uncertainty quantification, and practical interpretation.
Copula methods for modeling dependence, supervised feature selection, data augmentation, and biomedical classification. This work connects flexible dependence structures with statistical machine learning and predictive analytics.
CURRENT WORK
Current methodological projects address complex longitudinal dependence and efficient Bayesian comparison of positive-valued outcomes.
Developing copula-based neural transition methods for repeated measurements collected at irregular time points, with an applied focus on changes in oral-health status over time.
Studying computationally efficient approximate Bayesian procedures for two-sample comparisons under flexible two-parameter lifetime models, including mean and percentile-based estimands.
PROFILE & MENTORSHIP
Assistant Professor of Statistics
Dr. Murshed earned his Ph.D. in Statistics from the University of Louisiana at Lafayette. His dissertation, advised by Dr. Kalimuthu Krishnamoorthy, was titled Tests and confidence intervals based on data from independent sources. He earned an M.S. in Statistics from Ball State University, where his thesis examined Bayesian predictive modeling for personalized breast cancer treatment selection. He also earned an M.S. and B.S. from the University of Dhaka.
His research experience includes developing an R package for confidence intervals based on combined tests, building RNA-seq analysis pipelines, analyzing differential gene expression, and supporting public-policy studies involving seafood markets and early-childhood educator retention.
His scholarship now centers on statistical inference, statistical machine learning, predictive modeling, meta-analysis, cancer survival, health disparities, and copula-based methods. His work has appeared in Scientific Reports, Statistical Methods in Medical Research, the Journal of Statistical Theory and Practice, and other peer-reviewed journals.
Dr. Md Monzur Murshed received this award through the Minnesota State University, Mankato and Mayo Clinic Health System Seed Grant Program. The funded project evaluates the comparative effectiveness of Medtronic Intellis™ and Inceptiv™ spinal cord stimulation systems using patient-reported outcomes.
Ongoing student research associated with the Janovy Summer Research Award from the Chesley Center on Aging.
Co-author of the Kendall Hunt textbook used for Elementary Statistics at Minnesota State University, Mankato. ISBN 979-8-7657-1587-1.
View textbookCurrent Student Researcher
Inflammatory Breast Cancer: SEER analysis of racial disparities and survival outcomes. The manuscript is under review at Scientific Reports.
Research on Aging: Ongoing research using statistical and machine-learning methods to study aging-related health outcomes.
Former Graduate Student
Tonsillar Cancer Survival: Completed a SEER analysis of predictors of survival in tonsillar squamous cell carcinoma. She later entered a Ph.D. program at Iowa State University.
Former Student Researcher
Lung Cancer Outcomes: Studied stage-specific overall and relative survival and prognostic factors in lung cancer using SEER data. He later joined a high school as an instructor.
Former Undergraduate Researcher
Machine Learning Analysis of Maternal Health Risk Factors. Supported by a $1,500 Undergraduate Research Fund award.
Former Undergraduate Researcher
Simulation and Analysis of Infectious Disease Spread Using an SIR Model in R.
Courses taught at Minnesota State University, Mankato.
STAT 354, Concepts of Probability and Statistics
STAT 154, Elementary Statistics
STAT 354, Concepts of Probability and Statistics
STAT 356, Introduction to Programming
STAT 154, Elementary Statistics
STAT 455/555, Theory of Statistics I
STAT 154, Elementary Statistics
STAT 221, Applied Probability and Statistics for Engineers
STAT 456/556, Theory of Statistics II
STAT 492, Statistics Capstone Experience
STAT 354, Concepts of Probability and Statistics
STAT 457/557, Sampling Methods
STAT 154, Elementary Statistics, two sections
R, SAS, MATLAB, FORTRAN, Minitab, SPSS, STATA, StatCalc, LaTeX, Excel, and PowerPoint.
Dissertation Completion Fellowship, SGA Scholarship, graduate honors, Dr. Mir Masoom Ali Scholarship, NST Scholarship, University of Dhaka Dean’s Award, ASA, and AMS.
SCHOLARSHIP
Peer-reviewed publications and manuscripts currently under journal review.
Agnideep Aich, Sameera Hewage, and Md Monzur Murshed
Scientific Reports
Agnideep Aich, Md Monzur Murshed, Sameera Hewage, and Amanda Mayeaux
Scientific Reports, 16, 12132
Md Mahadi Hasan, Md Monzur Murshed, and Md Nahid Hasan
Electronic Research Archive, 34(9), 6957–6998
Md Mahadi Hasan, Md Monzur Murshed, and Md Nahid Hasan
Research in Statistics, 4(1), 2687308
M. M. Murshed and K. Krishnamoorthy
Journal of Statistical Theory and Practice, 18, 32
K. Krishnamoorthy, S. Lv, and M. M. Murshed
Communications in Statistics, Simulation and Computation
K. Krishnamoorthy and M. M. Murshed
Statistical Methods in Medical Research, 33, 42–60
D. Lazar, M. Begum, M. Murshed, M. Nelson, J. Bock, M. Imboden, L. Kaminsky, and A. Montonye
Journal of Biomedical Analytics, 3(1), 27–50
M. Islam, A. Akhtar, S. Munira, S. Khan, and M. M. Murshed
International Journal of Statistics and Probability, 7(5), 19–27
Student-led research supervised by M. M. Murshed
Scientific Reports
Agnideep Aich, Md Monzur Murshed, Bruce Wade, and Sameera Hewage
Preprint available on arXiv
CONTACT
Students and collaborators interested in statistical methodology, machine learning, health research, cancer outcomes, or aging research are encouraged to get in touch.
Dr. Md Monzur Murshed
Assistant Professor of Statistics
Department of Mathematics and Statistics
Minnesota State University, Mankato
Wissink Hall 262
(507) 389-6917
mdmonzur.murshed@mnsu.edu