Nilanjan Chatterjee, Ph.D.
|Organization:||National Cancer InstituteDivision of Cancer Epidemiology & Genetics, Biostatistics Branch|
|Address:||Executive Plaza SouthRoom 8020|
Dr. Chatterjee is the Chief and a Senior Investigator of the Biostatistics Branch of the Division of Cancer Epidemiology and Genetics (DECG), National Cancer Institute (NCI). He has received his Bachelor’s and Master’s degree from the Indian Statistical Institute, Calcutta and a PhD in Statistics from the University of Washington, Seattle in 1999. At NCI, his research focuses on a diverse set of quantitative issues that arise in design, analysis, interpretation and public health translation of modern molecular and genetic epidemiologic studies. He has made methodological contributions in cutting-edge topics such as analysis of genetic associations and gene-environment interactions, modeling etiologic heterogeneity by disease subtypes and development of models for risk prediction. He has played key roles in design and analysis of genome-wide association studies of various cancers with a particular emphasis on smoking related sites, such as lung and bladder. He is an active mentor for a number of Fellows and junior investigators and provides guidance for many ongoing projects in various areas such as risk-modeling, gene-environment interaction, design and analysis of studies that use next-generation sequencing. He is an elected Fellow of the American Statistical Association (2008), an elected member of the American Epidemiologic Society (2012) and is the recipient of numerous national and international awards, including the Mortimer Spiegelman Award (2010) for outstanding contribution to public health statistics, the Snedecor Award (2011) for significant contribution to theory of Biometry and the notable COPSS President’s award (2011) jointly sponsored by five major statistical societies to recognize the outstanding contribution by a young statistician.
Dr. Chatterjee has developed an integrated program of methodological and collaborative research for investigation of genetic and environmental causes of cancers. His primary foci of current research include studies of genetic association and gene-environment interactions, investigation of etiologic heterogeneity among cancer subtypes, risk prediction models and their applications to personalized medicine and cost-effective epidemiologic study designs. His statistical areas of research, which cut across the different scientific disciplines, include regression analysis under complex sampling designs (e.g case-control and two-phase sampling), meta-analysis, missing data, survival analysis, semi-parametric inference and shrinkage estimation.