Nima is an NSF postdoctoral research fellow in biostatistics at Weill Cornell Medicine, working with Iván Díaz and collaborating with David Benkeser. He just completed my PhD in biostatistics at UC Berkeley, under the guidance of Mark van der Laan and Alan Hubbard. Read more
Nima’s research interests sit at the intersection of nonparametric causal inference and machine learning, particularly in the development of statistical procedures tailored for efficient estimation and robust inference, in flexible statistical models. Broadly, he is motivated by methodological issues arising from high-dimensional inference, loss-based estimation, semiparametric theory, and complex study designs, usually inspired by applications in computational biology, epidemiology, and vaccine trials. He is also complementarily interested in high-performance statistical computing, research software engineering, and open source software for applied statistics.
