Sunil Mathur, Ph.D., MBA Associate Professor of Epidemiology and Biostatistics Contact information: skmathur@memphis.edu Phone: 901-678-3702 Robison Hall 222

Education:

• 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:

• Editor, PLOS ONE
• Editorial Board Member, International Journal of Medicine and Public Health
• Associate Editor, International Journal of Statistics and Systems
• Associate Editor, Global Journal of Pure and Applied Mathematics

Research Interests:

• 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 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. Dr. Mathur wrote a book Statistical Bioinformatics with R, Academic Press, USA in January 2010. His research interests include public health, nonparametric statistics, likelihood procedures, genomics, epidemiology, and biostatistics. In some of the papers (Mathur and Smith, 2007; Mathur and Dolo, 2007; Bokka and Mathur, 2006; Mathur, 2005; Sen and Mathur, 1997, 2000), his group has proposed new methodologies for analyzing complex multivariate data. Currently he is working in the area of cancer research. Cigarette smoking is the leading preventable cause of death and disease in the world and new effective efforts to reach smokers must be explored. Dr. Mathur is working with his collaborators to assess the role of cancer information seeking behavior in developing and disseminating effective smoking cessation strategies. In another study, Dr. Mathur’s group found that the cancer history of first-degree relatives (parents, siblings, and offspring) of all-age cancer patients, play an important role suggesting a familial contribution to cancer. The associations of family health history (FHH) with specific cancer sites including brain, breast, colon/rectum, genital, lip/oral, kidney cancer, and testicular teratomas have been shown in many studies. Most of the childhood cancers have been associated with FHH but a precise etiologic link yet to be firmly established. Since parental non-malignant diseases and cancer may be transmitted to children through inheritable DNA, Dr. Mathur is working with his collaborators to determine whether FHH may play a major role in increased childhood cancer risk among urban children. He is also working in the area of proteomics. The aim of Dr. Mathur’s research is to determine the specific proteins and their abundance and compare them across different experiments (patients), outcomes, and treatment groups, and then find protein markers for the disease. His work will enable researchers in medical field to identify these protein signatures and hence help the researchers to develop targeted drugs and cure the disease in more effective ways. Dr. Mathur’s work in the area of nonparametric inference has focused on bivariate and multivariate location problems. In some of the papers, he has proposed new methodologies for analyzing data using nonparametric procedures. Three students have completed their Ph.D. under Dr. Mathur’s supervision. He is Associate Editor of two international journals, editorial board member of a journal, and a reviewer for several international journals.