Kei-Hoi Cheung, PhD
Cards
About
Titles
Professor of Biomedical Informatics & Data Science
Professor, BiostatisticsBiography
Kei-Hoi Cheung, PhD has distinguished himself as a researcher and educator in the field of Biomedical Informatics with a growing national and international reputation. A particular strength is Dr. Cheung’s ability to forge strong, productive collaborations with a range of different bioscience researchers at Yale, in which his contributions include the development of complex databases and informatics tools that are critical for the research projects being performed. In the context of these collaborations, Dr. Cheung is simultaneously able to carry out his own informatics research on issues involved in robust interoperation and integration of databases and tools in the biosciences. In addition to giving talks and presentations at national and international meetings, he has published his own informatics research in peer-reviewed journals and conference proceedings, as well as contributing to publications focused on his collaborators’ research. He has established a broad base of collaborations with faculty in different departments at Yale, including Genetics, Pathology, Computer Science, Biostatistics, Molecular Biophysics and Biochemistry, and Biology. He was Director of Biostatistics and Bioinformatics Core of the NIDA Proteomics Center, focused on collaborative informatics support of neuroproteomics research at Yale. In addition to being a collaborator on numerous grants, Dr. Cheung has been PI on several federal grants (NIH and NSF). Dr. Cheung is also a core faculty member of Yale's Ph.D. Program in Computational Biology and Bioinformatics.
Dr. Cheung’ s research interests include the semantic web using the next generation of web technologies to integrate life science data and tools, and is co-editor of two books for Springer-Verlag titled: “Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences” and “Semantic e-Science”, respectively. Dr. Cheung also led the BioRDF task force (2008-2010) of the Semantic Web for Health Care and Life Sciences Interest Group that is an international community engaging in the creative use of Semantic Web in biomedicine. In addition, Dr. Cheung has recently embarked on natural language processing (NLP) projects in annotating, extracting and retrieving information from clinical text as part of the Veteran Administration (VA) electronic medical records. In summary, Dr. Cheung’s biomedical informatics expertise in database/semantic web research and NLP tool development, his national and international recognition as a researcher/educator, and his research contributions in these areas exemplify the attributes of a prominent researcher in biomedical informatics.
Appointments
Biomedical Informatics & Data Science
ProfessorPrimaryBiostatistics
ProfessorSecondary
Other Departments & Organizations
- Alzheimer's Disease Research Center (ADRC)
- Biomedical Informatics & Data Science
- Biostatistics
- Center for Biomedical Data Science
- Center for Medical Informatics
- Computational Biology and Biomedical Informatics
- Computational Biology and Bioinformatics
- Emergency Medicine York Street Campus Faculty
- NIDA Neuroproteomics Center
- Proteomics
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)
- Yale School of Public Health
- Yale Superfund Research Center
- Yale Ventures
Education & Training
- PhD
- University of Connecticut, Computer Science (1998)
Research
Overview
Ongoing Projects:
- Yale Protein Expression Database (YPED). YPED is an institution-wide database for use by proteomics researchers at Yale and outside of Yale
- Human Immunology Project Consortium (HIPC). HIPC was established by NIAID, which generates a wide variety of phenotypic and molecular data from well-characterized patient cohorts, including genome-wide
expression profiling, high-dimensional flow cytometry and serum cytokine concentrations. The adoption and adherence
to data standards is critical to enable data integration across HIPC centers, and facilitate data re-use by the wider scientific community. One key component of HIPC involves data standardization effort, along with the infrastructure that has been developed. - Center for Expanded Data Annotation and Retrieval (CEDAR). CEDAR is part of the Big Data to Knowledge (BD2K) initiative funded by NIH. It studies the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse.
- Clinical Natural Language Processing (NLP). To extract and retrieve information from large amounts of clinical notes (unstructured data) for facilitating clinical research, a variety of NLP techniques including the incorporation of ontologies have been explored in different domains including lung/colon cancer, post-traumatic stress disorder, psychogenic nonepileptic seizure, and chronic pain.