David Shih joined the School of Biomedical Informatics in December 2020, following a postdoctoral fellowship in Systems Biology at MD Anderson Cancer Center, where he investigated therapeutic strategies to exploit cancer defects in DNA damage repair using pharmacogenomic data. Previously during his doctoral studies, he characterized the genomics of pediatric brain tumors in order to identify molecular classes, cancer driver genes, aberrant molecular pathways, and prognostic biomarkers. Dr. Shih was also a postdoctoral fellow in the Department of Data Science at Dana-Farber Cancer Institute, with cross-appointments in the Department of Biostatistics at Harvard T.H. School of Public Health and at the Broad Institute. During this fellowship, he studied the molecular evolution of brain metastases and developed novel methodologies for case-control DNA copy-number analysis.
Dr. Shih’s current research focuses on developing tailored statistical models and computational algorithms in order to derive insights from high-throughput genomics, sequencing, and electronic health record data. He is particularly interested in developing statistical models that are tailored to the data and accelerated by variational autoencoders. In this way, this framework can benefit from the rigor and interpretability of statistical models as well as the flexibility and efficiency of deep learning techniques.
“Genomic technologies provide unprecedented volumes of molecular data, and my work helps turn these data into opportunities for unraveling complex diseases.”
* These authors contributed equally