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These talented researchers have been hired to support the growing demand for HDSI’s academic programs and to expand upon the robust interdisciplinary data science research happening across UC San Diego.
“HDSI continues to attract highly regarded researchers in all areas of data science,” said founding director Rajesh K. Gupta. “The new appointments reflect growth in core areas of Data Science such as Machine Learning, Mobile Health, Privacy, and Statistics but also interdisciplinary areas such as Genetics and Environmental Data Science, which is the subject of an ongoing search.”
The new faculty members are leaders in their respective spheres and will host courses in several areas of research, including machine learning, statistics, biomedical informatics, and applied math. They join roughly 50 colleagues with full or partial appointments with HDSI. For a full list please visit https://datascience.ucsd.edu/about/faculty/faculty/.
HDSI continues to recruit additional faculty members with several searches presently underway.
Founded in 2018 as an independent academic unit at UC San Diego, the mission of the Halıcıoğlu Data Science Institute is to establish the scientific foundations of data science, develop new methods and infrastructure, and train students and partners to use data science to solve the world’s most pressing problems. The institute is the administrative home of the undergraduate major and minor in data science, as well as three graduate-level data science programs (MS, Ph.D., online MDS).
AY2022-2023 New Faculty:
Tiffany Amariuta, Assistant Professor
Ph.D.: Harvard University
Before starting her lab in San Diego, Tiffany earned a B.S. in Biological Engineering at MIT and went on to conduct graduate research with Dr. Soumya Raychaudhuri as part of the Bioinformatics and Integrative Genomics Ph.D. program at Harvard Medical School, where she studied the genetic susceptibility of autoimmune diseases and other polygenic diseases. During graduate school, Tiffany developed machine learning methods to predict the functionality of regulatory variants, which had applications to transcription factor binding prediction, eQTL mapping, heritability enrichment analysis, and trans-ancestry portability of polygenic risk scores. Dr. Amariuta has a joint appointment with the Department of Medicine.
Biwei Huang, Assistant Professor
Ph.D.: Carnegie Mellon University
Biwei Huang’s research interests are mainly in three aspects: (1) automated causal discovery in complex environments with theoretical guarantees, (2) advancing machine learning from the causal perspective, and (3) using or adapting causal discovery approaches to solve scientific problems. She successfully led a NeurIPS’20 workshop on causal discovery and causality-inspired machine learning and co-organized the first Conference on Causal Learning and Reasoning (CLeaR 2022). She was named a Rising Star of the Trustworthy ML Initiative and is a recipient of the Presidential Fellowship at CMU in 2017 and the Apple Scholars in AI/ML Ph.D. fellowship in 2021.
Haojian Jin, Assistant Professor
Ph.D.: Carnegie …….