Awards and Promotions

Jordan Dworkin

Jordan Dworkin, PhD, joined Mental Health Data Science as an Assistant Professor in July 2020 after receiving his PhD in Biostatistics from the University of Pennsylvania. His expertise lies primarily in statistical methods for neuroimaging data, with a focus on the development of diagnostic and prognostic tools for structural imaging in neurological disorders. Through this research, he has worked on both data- and theory-driven methods for locating medically relevant signals within high-dimensional data structures. More recently, Jordan has collaborated on a variety of projects spanning developmental psychiatry, network analysis, and science of science; this work has contributed to a growing interest in complex systems and multidomain data.

Jordan is thrilled to have the opportunity to work with the Columbia Mailman School Biostatistics Department; he is excited to learn from the group’s wide-ranging areas of expertise and to contribute to its drive for equity and opportunity among emerging scholars in public health and statistics.

Iuliana Ionita-Laza

We congratulate Iuliana Ionita-Laza, PhD, on her promotion to Professor of Biostatistics, with tenure, in January 2021. Iuliana received her PhD in 2006 from the Courant Institute of Mathematical Sciences at NYU and has been a member of the Department since 2009. Her main research interests lie at the interface of statistics and genomics. She is particularly interested in developing statistical and machine learning methods for the analysis of high-dimensional genetic and functional genomics data. She is also involved in applications of such methods to understand the genetic basis of complex diseases and traits, including autism spectrum disorders, schizophrenia, and Alzheimer's disease. She has been the PI of multiple grants from NIH and NSF and serves on the editorial boards of Biometrics and Statistics in Biosciences. She is also a regular member of the NIH Genomics, Computation and Technology (GCAT) study section. She teaches a course of statistical methods in genomics, and several short courses.  

She is currently leading a genomics program that brings together an interdisciplinary group of people from multiple departments across Columbia University with diverse research expertise in statistical/computational genomics and other omics, computational biology, biomedical informatics, and an interest in understanding biology and human health. Through various activities including regular seminars and working groups, the program aims to increase research and learning opportunities, and benefit students and postdocs through interdisciplinary training in quantitative genomics. More information can be found on the program’s website. Together with Andrea Baccarelli and Gary Miller, she leads a mentoring/training grant in data science and omics (Career MODE) for early-stage career individuals. More information can be found on the Career MODE website.

Yifei Sun

Congratulations to Yifei Sun, PhD, for receiving the Outstanding Young Researcher Award from the International Chinese Statistical Association (ICSA). She was selected to receive the award “for her important and outstanding research for lifetime data science, in particular, her novel contribution for recurrent event analysis, stochastic lifetime processes, biased sampling, and predictive modeling,” according to the ICSA.

Yifei’s research focuses on the development of a decision-theoretic framework for decision tree learning for time-to-event outcomes and semiparametric event history analysis using electronic health records data.