Jelena Bradic is an Associate Professor of Statistics at the
Department of Mathematics & Halicioglu Data Science Institute
associated with the University of California, San Diego.
In the period of 2007-2011, Prof. Bradic was very fortunate to work with Prof. Jianqing Fan at Princeton University, while completing her Ph.D. work in Statistics at the Department of Operations Research and Financial Engineering (ORFE). In 2011 she joined Department of Mathematics at University of California, San Diego as an Assistant Professor.
Prof. Bradic directs "Statistics Lab for Causal and Robust Machine Learning". Her interests are in causal inference, machine learning, robust statistics as well as missing data problems. Her application areas include observational and interventional data, treatment effects, as well as public health and policy learning. She strives to understand and develop new robust learning methods and algorithms with provable guarantees of stability, robustness to data corruption and data generating mechanism.
Prof. Bradic is a current Associate Editor of
The Journal of the American Statistical Association: Theory & Methods
The Journal of Nonparametric Statistics
The Scandinavian Journal of Statistics
Prof. Bradic has been elected
Program Chair 2020
for the ASA Section on Statistical Learning & Data Science
& Statistical Learning and Data Science Conference, March, 2020 @ UC Irvine.
Department of Mathematics & Halicioglu Data Science Institute
associated with the University of California, San Diego.
In the period of 2007-2011, Prof. Bradic was very fortunate to work with Prof. Jianqing Fan at Princeton University, while completing her Ph.D. work in Statistics at the Department of Operations Research and Financial Engineering (ORFE). In 2011 she joined Department of Mathematics at University of California, San Diego as an Assistant Professor.
Prof. Bradic directs "Statistics Lab for Causal and Robust Machine Learning". Her interests are in causal inference, machine learning, robust statistics as well as missing data problems. Her application areas include observational and interventional data, treatment effects, as well as public health and policy learning. She strives to understand and develop new robust learning methods and algorithms with provable guarantees of stability, robustness to data corruption and data generating mechanism.
Prof. Bradic is a current Associate Editor of
The Journal of the American Statistical Association: Theory & Methods
The Journal of Nonparametric Statistics
The Scandinavian Journal of Statistics
Prof. Bradic has been elected
Program Chair 2020
for the ASA Section on Statistical Learning & Data Science
& Statistical Learning and Data Science Conference, March, 2020 @ UC Irvine.
Prof. Bradic has been awarded a 2017 NSF DMS Grant (sole PI), awarded by the NSF Division of Mathematical Sciences, a 5-year partnership with Scientific Research Community of the Research Foundation Flanders (FWO), she is the recipient of the 2014 Hellman Fellowship, awarded by the Hellman Foundation, she has been awarded a 2012 NSF DMS Grant award (sole PI), awarded by the NSF Division of Mathematical Sciences, she has been the recipient of the 2012 WCAI Research Grant Award, awarded by the University of Pennsylvania and the 2010 LAHA Award, awarded by the Institute of Mathematical Statistics. Prof. Bradic has been recognized as an outstanding teacher at Princeton University with APGA Award for Teaching and Scholarly Excellence and an Excellence in Teaching Award. She currently serves on committees for National Science Foundation and the American Statistical Association.
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