About Jiang Bian
Biomedical Informatics is an interdisciplinary field, where the central theme is to explore the effective uses of data, information, and knowledge for scientific inquiry, problem-solving, and decision making, motived by efforts to import human health. I have a diverse yet strong multi-disciplinary background in data integration, semantic web, machine learning, natural language processing, social media analysis, network science, data privacy, and software engineering. Nevertheless, my expertise and background serve an overarching theme: data science with heterogeneous data, information and knowledge resources.
I currently serve as the Chief Data Scientist and Chief Research Information Officer for UF Health, Division Chief of Biomedical Informatics in Health Outcomes & Biomedical Informatics, Director of the Biomedical Informatics Program for the UF Clinical and Translational Science Institute (CTSI; https://www.ctsi.ufl.edu/about/ctsi-programs/biomedical-informatics/), Director of Cancer Informatics Shared Resource (and its eHealth Core program http://bit.ly/36IBw5s jointly supported by the UF CTSI), and the Chief Data Scientist for the OneFlorida+ Clinical Research Consortium (https://onefloridaconsortium.org/).
I have a diverse yet strong multi-disciplinary background. Nevertheless, my expertise and background serve an overarching theme: data science with heterogeneous data, information and knowledge resources. My research areas can be divided into two logical sections under this overarching theme: (1) data-driven medicine—applications of informatics techniques, including AI/ML methods in medicine on solving big heterogeneous data problems, providing insights into health-related behavior and health outcomes of various populations and finding ways to develop interventions that promote public and consumer health; and (2) development of novel informatics methods, tools, and systems to support clinical and clinical research activities such as tools for data integration and harmonization, clinical trial design, and cohort discovery.
Google Scholar: https://scholar.google.com/citations?hl=en&user=ysr–voAAAAJ&view_op=list_works&sortby=pubdate
- Cancer Informatics
- Social media
- data privacy in healthcare
- data science
- eHealth and user-centered design
- semantic web