Fuhai Li, PhD

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  • Calculated based on no. of publications stored in Pure and citations from Scopus
20052021

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Personal profile

Personal profile

Dr. Fuhai Li received his Ph.D. in applied mathematics at Peking University, and did his pre-doctoral and postdoctoral training in Bioinformatics at Harvard Medical School and Houston Methodist Research Institute. Dr. Li has more than seven years of training and experience in bioinformatics on several research projects funded by NIH, DoD, CPRIT, and other public and private funding sources. He aims to bring better patient care and drug development through his highly collaborative research in bioinformatics and computational biology in the emerging field of big data to knowledge. In particular, he aims to address technical and computational challenges in solving disease problems, including: precision medicine for biomarker identification, drug repositioning, drug combination discovery, and personalized drug response prediction by integrating and analyzing large-scale genomic, imaging, clinical, and environmental data; and tumor-microenvironment interaction modeling to uncover and model the roles of the tumor-niche interactions in tumor development, metastasis, and drug resistance through the integration of genomics and imaging data.

Research interests

Systematic integration of diverse and heterogeneous data resources and subsequent discovery of the embedded knowledge from integrative datasets requires the combination of advanced mathematical approaches and domain knowledge in biomedicine. This emerging field fits extremely well with his experience, expertise, and research interests. Through Dr. Li's highly collaborative research in bioinformatics and computational biology in the emerging field of big data, he aims to bring better patient care to the clinic and enhance drug development In particular, he aims to address technical and computational challenges through use of

-Precision medicine for biomarker identification, drug repositioning, and drug combination discovery
-Personalized drug response prediction by integrating and analyzing large-scale genomic, imaging, clinical, and environmental data
-Tumor-microenvironment interaction modeling to uncover and model the roles of the tumor-niche interactions in tumor development, metastasis, and drug resistance through the integration of genomics and imaging data

Education/Academic qualification

Postdoctoral Fellowship, Harvard Medical School

Radiology, Postdoctoral Fellowship, Houston Methodist Research Institute

Applied Mathematical Sciences, PhD, Peking University

External positions

Assistant Professor of Biomedical Informatics, The Ohio State University

Feb 2016 → …

Research Area Keywords

  • Systems Medicine & Bioinformatics
  • Cancer

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