Jason H. Moore, Ph.D.
Dr. Moore is the scientific director and principle investigator of EBIC. His background and expertise is at the intersection of computer science, statistics, and the biological sciences with a focus on genetics and genomics. He leads the NIH-funded Computational Genetics Laboratory that develops innovative computational methods for solving complex problems across the biomedical sciences using artificial intelligence, machine learning, and visual analytics. He also serves as director of the Penn Institute for Biomedical Informatics.
Zhiping (Paul) Wang, Ph.D.
Dr. Wang is the technical director for EBIC. He has a Ph.D. in Computer Science from Indiana University and has more than 15 years of experience working in the development and application of bioinformatics methods and pipelines for the analysis of next-generation sequence data. Dr. Wang is available to meet with CEET investigators to discuss and manage environmental health science projects that need bioinformatics support.
Taehyong Kim, Ph.D.
Dr. Kim graduated in Computer Science from State University of New York at Buffalo followed by postdoctoral training at Stanford University. He will oversee all CEET web programming and database/application development projects, develop solutions and mentor the other EBIC bioinformaticians to implement such solutions for these projects.
Maggie Lu, Ph.D.
Dr. Lu was trained in Genetics, Genomics and Bioinformatics in the University of California, Riverside. She will work with the technical director to complete NGS data analysis, bioinformatics application development, web and database development, and other biomedical data analysis.
Jerome Lin, M.S.
Mr. Lin was trained in the Department of Human Genetics, University of Pittsburgh, focusing on bioinformatics research. He has extensive experience in bioinformatics, machine learning, and protein research etc.
Selah Lynch, M.S.
Ms. Lynch is trained in computer and information sciences at the University of Pennsylvania and is an expert in the retrieval and analysis of clinical data from the Electronic Health Record. She has considerably experience with data cleaning, data integration, and data analysis using machine learning and visual analytics.