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Sunil Mathur
Sunil Mathur
Sunil Mathur, Ph.D. M.Phil., M.Sc., MBA
Associate Professor of Epidemiology and Biostatistics
Contact information:
Phone: 901-678-3702
Robison Hall 222


  • Ph.D. (Statistics), M.Phil (Statistics), M.Sc. (Statistics), B.Sc. (Math) University of Delhi, India
  • MBA, Indira Gandhi National University
  • Certified training in SAS, SPSS, and SAP, USA
  • Certified training in Computer Programming and System Design

Professional Services:

  • Editorial Board Member, PLOS ONE
  • Editorial Board Member, Global Journal of Medicine and Public Health
  • Editorial Board Member, Journal of Translational Medicine & Epidemiology
  • Associate Editor, International Journal of Statistics and Systems
  • Associate Editor, Global Journal of Pure and Applied Mathematics
  • Referee for international journals

Research Interests:

  • Childhood Obesity
  • Cancer Communication, Perception, and Prevention
  • Biostatistics
  • Genomics
  • Public Health
  • Epidemiology

Recent Publications:

Book: Statistical Bioinformatics with R, Academic Press, USA, January 2010.
Mathur, S.K., and Levy, M. (2013). Association of Lung Cancer Perception and Distress among Smokers, Former Smokers and Never Smokers: Moderating Role of Physical Activity and Race. Epidemiology Biostatistics and Public Health (Formerly Italian Journal of Public Health), 10(2), DOI: 10.2427/8839. (Click here to view article)
Mathur, S.K., Levy, M., and Stafford, M.B.R (2013). The Role of Cancer Information  Seeking Behavior in Developing and Disseminating Effective Smoking Cessation Strategies: A Comparison of Current Smokers, Former Smokers and Never Smokers. Journal of Communication in HealthCare, 6(1), 61-70. (Click here to view article)

Mathur, S. K. and Sepehrifar, M. (2012). A New Signed Rank Test Based on Slopes of Vectors for Bivariate Location Problems. Statistical Methodology, Accepted for Publication, DOI: 10.1016.

Mathur, S.K., and Sadana, A. (2011). Finding Differentially Expressed Genes in High Dimensional Data: Rank Based Test Statistic via a Distance Measure. Statistical Methods in Medical Research. Accepted for publication, DOI: 10.1177/0962280211434428.

Mathur, S. K. (2009). A Run based Procedure to Identify Time-lagged Gene Clusters in Microarray Experiments. Statistics in Medicine, 28 (2), 326-337.

Mathur, S.K. (2009). A New Nonparametric Bivariate Test for Two-Sample Location Problem. Statistical Methods and Applications, 18 (3), 375-388.

Murthy, S.S., Kiran, V.S.R, Mathur, S.K., and Murthy, S. (2008). Noninvasive Transcutaneous Sampling of Glucose by Electroporation. Journal of Diabetes Science and Technology, 2(2), 250-254.

Mathur, S.K., and Smith, P.F. (2008). An Efficient Nonparametric Test for Bivariate Two-Sample Location Problem, Statistical Methodology, 5 (2), 142-159.

Mathur, S.K. and Dolo, S. (2008). A new Efficient Statistical Test for Detecting Variability in the Gene Expression Data, Statistical Methods in Medical Research, 17, 405-419.

Recent Accomplishments and Honors:

Faculty Research Fellow Award, University of Mississippi, 2006, and 2007
First Prize, Sigma Xi Research Poster Competition, University of Mississippi, 2007

Dr. Mathur’s research interests focus on both biostatistical applications and methodological development of biostatistics. His research interests include childhood obesity, cancer research, public health, nonparametric statistics, likelihood procedures, genomics, biostatistics, and epidemiology. In the area of pediatric obesity, the number of children who are overweight and obese is increasing rapidly world-wide, and the World Health Organization has declared obesity as one of the largest epidemics of modern times. In order to combat the epidemic of childhood obesity, there is a pressing need to understand the association among different factors (genetic and non-genetic) and childhood obesity. We are working to establish the association of several factors and obesity among children and examine the moderating role of birth weight, race, and maternal smoking status during pregnancy. Dr. Mathur is working in the area of lung cancer which is a second most common cancer among men and women (American Cancer Society, 2011), making it as a leading cause of death in the Unites States. He is exploring the association of lung cancer perception and other factors and examining the effects of physical activity and race on this association. He is also exploring other factors that may affect risk perception of lung cancer. In genomics, his application work is motivated by the recent developments in the analysis of genomic data where the sample sizes are usually very small and it is hard to make any distributional assumptions regarding the underlying data. Through his application work, he has found solutions to some of the complex problems in genomics, and developed statistical test procedures to identify differentially expressed genes. These test procedures are efficient as compared to their competitors and one of the unique qualities of these procedures is that they can be applied even when the sample size is small or distribution is unknown. In the nonparametric inference, he has been working on bivariate and multivariate location problems. In some of the papers, he proposed new methodologies for analyzing bivariate data using nonparametric procedures. He gives importance to setting up successful collaborations, and always welcomes new collaboration opportunities.

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