I am an Associate Professor in the Department of Statistics and Operations Research at Tel Aviv University.
I develop statistical methods for causal inference in complex settings. My research combines methodological work with collaborations in medicine, epidemiology, economics, and machine learning, including the use of causal methods to understand how language models make predictions.
Available for seminar introductions, conference programs, and professional profiles.
Daniel Nevo is an Associate Professor in the Department of Statistics and Operations Research at Tel Aviv University. He develops statistical methods for causal inference and survival analysis, with particular interests in network interference, event-time outcomes, causal diagnostics, and generalizability. His work is motivated by collaborations in medicine, epidemiology, public health, economics, and computer science. He received his PhD in Statistics from the Hebrew University of Jerusalem and completed postdoctoral training in Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health.
I’m back at Tel Aviv University after my 2025–2026 sabbatical as an MIT-Kalaniyot Sabbatical Scholar at MIT’s Institute for Data, Systems, and Society (IDSS), and a Faculty Visitor in Harvard University’s Department of Statistics.
Published with S. Girgin, O. Erez, and R. Raz in International Journal of Epidemiology.
Work led by PhD student Bar Weinstein. Published in Biostatistics.
Presented “Transportability and Generalizability of Causal Effects Under Network Interference” at the Joint Statistical Meetings in Boston.
Work led by PhD student Avi Baraz. Published with A. Cahan, T. Brosh-Nissimov, M. Chowers, and U. Obolski in BMC Medical Research Methodology.
A comment with M. Gorfine appeared in Biometrical Journal.
Work led by PhD student Tamir Zehavi. Published with U. Obolski and M. Chowers in Statistics in Medicine.
Her thesis is titled Identifying Influential Individuals in a Causal Network Through Random Effects Framework.
Published with O. Danieli, I. Walk, B. Weinstein, and D. Zeltzer in the American Economic Review.
Her dissertation is titled Topics in Causal Inference with Applications to Medical Data.