Jelena Bradic is a Full Professor at the UC San Diego, where she holds a joint appointment in the Department of Mathematical Sciences and Halicioglu Data Science Institute. She held the position of Associate and Assistant Professor at UCSD in 2018-2022 and 2011-2018, respectively. Prof. Bradic was also a Visiting Associate Professor at Stanford University's Statistics Department in 2019-2020.
Prof. Bradic holds a Ph.D. degree in Statistics from Princeton University (2011) associated with the Operations Research and Financial Engineering Department . She has had the pleasure to study under the guidance of Prof Jianqing Fan. Her undergraduate and masters degree are in Mathematics from Belgrade University, Serbia (2004, 2007).
Prof. Bradic's 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.
co Editor-in-Chief with Stratos Idreos(Harvard) and John Lafferty(Yale) of a new joint journal between ACM and IMS,
ACM/IMS Journal of Data Science: State tuned for more details.
Associate Editor of
The Journal of the Royal Statistical Society: Series B: 2020-
The Journal of the American Statistical Association: Theory & Methods: 2019-
The Journal of Nonparametric Statistics: 2019-
The Scandinavian Journal of Statistics: 2019-
Prof. Bradic has been elected
Program Chair 2021 of the ASA Section on Statistical Learning & Data Science
Program co-Chair for 2020 Statistical Learning and Data Science Conference (postponed due to Covid)
Prof. Bradic holds a Ph.D. degree in Statistics from Princeton University (2011) associated with the Operations Research and Financial Engineering Department . She has had the pleasure to study under the guidance of Prof Jianqing Fan. Her undergraduate and masters degree are in Mathematics from Belgrade University, Serbia (2004, 2007).
Prof. Bradic's 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.
co Editor-in-Chief with Stratos Idreos(Harvard) and John Lafferty(Yale) of a new joint journal between ACM and IMS,
ACM/IMS Journal of Data Science: State tuned for more details.
Associate Editor of
The Journal of the Royal Statistical Society: Series B: 2020-
The Journal of the American Statistical Association: Theory & Methods: 2019-
The Journal of Nonparametric Statistics: 2019-
The Scandinavian Journal of Statistics: 2019-
Prof. Bradic has been elected
Program Chair 2021 of the ASA Section on Statistical Learning & Data Science
Program co-Chair for 2020 Statistical Learning and Data Science Conference (postponed due to Covid)
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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