Hector Corrada Bravo
Hector Corrada Bravo is currently a postdoctoral fellow in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. His research centers on statistical and machine learning methods for high-throughput genomic data analysis, currently focusing on second-generation sequencing. He received his Ph.D. in Computer Sciences from the University of Wisconsin-Madison, where he was a recipient of a Ford Fellowship from the National Academies.
His work spans the full range of computational genomics analysis: from pre-processing of measurements from high-throughput assays to disease risk models that integrate high-throughput genomic and other data. Thus, his research interests include the development of new methods and tools from multiple areas in the computational and statistical sciences: basic bioinformatics/biostatistics, statistical and machine learning, data management and numerical optimization.
Dr. Bravo is joining the Computer Science department as an Assistant Prof essor of Computer Science, with a courtesy appointment in UMIACS.
