School of Medicine
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John A. Overdeck Professor, Professor of Statistics and of Biomedical Data Sciences
Current Research and Scholarly InterestsFlexible statistical modeling for prediction and representation of data arising in biology, medicine, science or industry. Statistical and machine learning tools have gained importance over the years. Part of Hastie's work has been to bridge the gap between traditional statistical methodology and the achievements made in machine learning.
Associate Professor of Medicine (Biomedical Informatics), of Biomedical Data Science, of Surgery and, by courtesy, of Epidemiology and Population Health
Current Research and Scholarly InterestsMy background and expertise is in the field of computational biology, with concentration in health services research. A key focus of my research is to apply novel methods and tools to large clinical datasets for hypothesis generation, comparative effectiveness research, and the evaluation of quality healthcare delivery. My research involves managing and manipulating big data, which range from administrative claims data to electronic health records, and applying novel biostatistical techniques to innovatively assess clinical and policy related research questions at the population level. This research enables us to create formal, statistically rigid, evaluations of healthcare data using unique combinations of large datasets.
Postdoctoral Scholar, Biomedical Data Sciences
BioZhi Huang received his Bachelor of Science degree in Automation (BS--MS straight entrance class) from Xi'an Jiaotong University School of Electronic and Information Engineering in June 2015. In August 2021, He received a Ph.D. degree from Purdue University, majoring in Electrical and Computer Engineering (ECE).
His background is in the area of Machine and Deep Learning, Computational Pathology, Computational Biology, and Bioinformatics.
From May 2019 to August 2019, he was at Philips Research North America as a Research Intern.