The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Mark J. van der Laan sits on this spectrum.
This scientist: 565 publications — 98th percentile
98% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 537 publications or more.
The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Mark J. van der Laan sits on this spectrum.
This scientist: 82 D-Index — 97th percentile
97% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 86 D-Index or more.
Mark J. van der Laan is affiliated with the University of California, Berkeley in the United States. Their research primarily spans the field of mathematics, with a strong focus on statistics and probability. This includes work in several subfields such as artificial intelligence, economics and econometrics, nutrition and dietetics, and psychiatry and mental health.
The scientist's key research topics include advanced causal inference techniques, statistical methods and inference, statistical methods and Bayesian inference, and statistical methods in clinical trials. Additional areas of focus cover health systems, economic evaluations, quality of life, as well as child nutrition and water access and feeding issues.
Van der Laan has published extensively in a variety of venues. Frequent publication sources include:
Their recent published papers include:
Van der Laan frequently collaborates with other researchers. Notable co-authors include:
The scientist received the COPSS Presidents' Award in 2005. The award recognized their contributions to theoretical and applied statistics across several domains such as multivariate survival analysis, semiparametric models, causal inference, dynamic treatment regimes, multiple testing, model selection, cross-validation loss-based estimation, and computational biology. This work is applied in fields involving high-dimensional data in epidemiology, genomics, and medical sciences.
Alan E Hubbard;Jennifer Ahern;Nancy L Fleischer;Mark Van der Laan
Mark J. van der Laan;Daniel Rubin
Maya L Petersen;Kristin E Porter;Susan Gruber;Yue Wang
Maya L. Petersen;Sandra E. Sinisi;Mark J. van der Laan
S A Murphy;M J van der Laan;J M Robins
Romain Pirracchio;Romain Pirracchio;Maya L Petersen;Marco Carone;Matthieu Resche Rigon
Cheng Ju;Aurélien Bibaut;Mark J. van der Laan
Nancy S Padian;Ariane van der Straten;Gita Ramjee;Tsungai Chipato
Mark J. van der Laan;Katherine S. Pollard;Jennifer Bryan
Merrill D. Birkner;Katherine S. Pollard;Mark J. van der Laan;Sandrine Dudoit
Sherri Rose;Mark J. van der Laan
Richard D. Gill;Mark J. van der Laan;James M. Robins
Bruce Fireman;Janelle Lee;Ned Lewis;Oliver Bembom
Mark J. van der Laan;Katherine S. Pollard
Mark J. van der Laan;Sandrine Dudoit
Erin LeDell;Maya L. Petersen;Mark J. van der Laan
Mark J. van der Laan;Susan Gruber
Maya L. Petersen;Mark J. van der Laan
Sandrine Dudoit;Mark J. van der Laan;Katherine S. Pollard
Sandra E. Sinisi;Eric C. Polley;Maya L. Petersen;Soo Yon Rhee
Mark J. van der Laan;Sandrine Dudoit;Katherine S. Pollard
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