Nallakkandi Rajeevan

Dr. Nallakkandi Rajeevan is a Senior Research Scientist in the Department of Biomedical Informatics & Data Science at Yale School of Medicine, where he also serves as Associate Director for Bioinformatics at the Yale Center for Medical Informatics. He holds additional affiliations with the Genomics, Genetics, and Epigenetics Program at Yale Cancer Center and the Yale-BI Biomedical Data Science Fellowship.

Dr. Rajeevan received his B.E., M.S., and Ph.D. from Indian Institute of Science, Bangalore, India, with educational background in Electrical Engineering and Electronics and Communications. He completed a post-doctoral fellowship in Nuclear Medicine from University of Massachusetts Medical Center in 1993.

His research focuses on applying theoretical computer science, algorithm development, statistical estimation theory, and biostatistics to problems in genomics, bioinformatics, nuclear medicine, and functional brain imaging. Dr. Rajeevan has established a robust research program analyzing veteran health data, particularly related to infectious diseases and post-acute outcomes. His work bridges computational methods with clinical applications to generate actionable insights for healthcare delivery and policy.

Dr. Rajeevan's recent publications (2023-2025) demonstrate a strong focus on methodologically rigorous studies of COVID-19 outcomes using target trial emulation approaches. His research spans vaccine effectiveness, post-COVID conditions, healthcare utilization patterns, and comparative mortality analysis across respiratory viruses, primarily using Veterans Health Administration data.

• Senior Member, Institute of Electrical and Electronics Engineers (IEEE), 2021
• Lifetime Service Award, Indo-American Society of Nuclear Medicine, 2010

Dr. Rajeevan maintains an active research program with numerous collaborations, particularly with researchers like Mihaela Aslan, Lei Yan, and Hongyu Zhao. His interdisciplinary approach combines computational expertise with clinical insights to address complex questions in public health and healthcare delivery, with particular emphasis on generating real-world evidence to inform clinical decision-making.