Nima Hejazi

Assistant Professor
Department of Biostatistics, Harvard T.H. Chan School of Public Health

Nima Hejazi, PhD, is an Assistant Professor of Biostatistics at the T.H. Chan
School of Public Health of Harvard University. He completed an NSF Mathematical
Sciences Postdoctoral Research Fellowship, and, before this, obtained his PhD in
Biostatistics from UC Berkeley. He was on the founding core development team of
the tlverse project (, an extensible ecosystem for
targeted learning in the R language, and, since 2020, has collaborated closely
with the Vaccine and Infectious Disease Division of the Fred Hutchinson Cancer
Center, as a core member of the US Government Biostatistics Response Team of the
COVID-19 Prevention Network and, more broadly, in studies of vaccine safety and
efficacy of HIV-1, malaria, and COVID-19.

Nima’s research interests combine causal inference and machine learning, driven
by the aim of developing tailored, assumption-lean statistical procedures for
efficient and robust inference about scientifically informative parameters. He
is motivated by methodological issues from robust non/semi-parametric inference,
high-dimensional inference, targeted loss-based estimation, and biased sampling
designs. His statistical research is strongly informed by collaborative work in
clinical trials and computational biology, especially as related to vaccine
efficacy and treatment trials, infectious disease epidemiology, and immunology.
Nima is also deeply interested in high-performance statistical computing and the
development of open source software for reproducible applied statistics.