Alok Dwivedi, PhD, MSc

Alok Dwivedi, PhD, MSc, is a professor and director of the Center for Biostatistics and Data Science Services (CBDS) within the Department of Biomedical Informatics, Biostatistics and Medical Epidemiology (BBME) at the University of Missouri School of Medicine. Dr. Dwivedi’s research is dedicated to advancing evidence-based and value-based biostatistical practices in biomedical research. He develops resources to enhance scientific rigor and promote best practices, aiming to elevate the quality of research and scholarship across disciplines. His clinical-epidemiological research focuses on understanding the complex interplay between endocrine-disrupting chemicals, sex hormones, metabolic stressors and neuropsychiatric symptoms for cardiac, dementia and cancer risk prevention in the context of sex differences.

Dr. Dwivedi applies and facilitates the integration of biostatistics, epidemiology, data science and informatics tools across a wide range of health research — spanning basic science, translational research and population health. His work supports the design, conduct, analysis and interpretation of health studies aimed at understanding disease etiology, health disparities and the effectiveness of interventions and treatments to enhance informed decision-making and improved patient care. As a collaborative and team scientist, Dr. Dwivedi provides methodological expertise in grant development and research studies. In addition, Dr. Dwivedi also develops robust methods and innovative tools for improving statistical skills, knowledge, innovation, efficiency and support across the scientific community. Dr. Dwivedi teaches and creates educational resources to train the next generation of researchers in the appropriate and rigorous application of biostatistics, epidemiology, research design and health informatics in clinical and translational science.

His clinical and epidemiological work incorporates intervention studies, secondary data analyses, systematic reviews, meta-analyses, and the development of prognostic models to accelerate scientific progress and impact in biomedical research.