Investigator, Howard Hughes Medical Institute
Distinguished Professor, Biomolecular Engineering, University of California
Santa Cruz Scientific Director, UC Santa Cruz Genomics Institute, University of California, Santa Cruz
Scientific Co-Director, California Institute for Quantitative Biosciences (QB3)
David Haussler develops statistical, algorithmic and experimental methods to explore molecular function and evolution in the human genome, integrating comparative and high-throughput genomics data to study gene structure, function, and regulation. He develops and shares infrastructure to support both basic research and medicine. In the 1990s, he pioneered the use in genomics of hidden Markov models, stochastic context-free grammars, neural networks and discriminative kernel methods, building some of the most successful computational methods to find genes in genome sequences and align them to detect evolutionary changes. As collaborators on the international Human Genome Project, his team created the first publicly available computational assembly of the human genome sequence and posted it on the Internet on July 7, 2000. They subsequently developed the UCSC Genome Browser, a web-based tool that has more than 10,000 users on average per day generating more than 1 million page requests.
His experimental research focuses on the molecular evolution of DNA, RNA, and protein sequences with a special emphasis on neurodevelopment and immunology. His lab uses CRISPR, cortical organoid, single cell RNA-seq and other technologies to functionally characterize neurodevelopmental genes that were specifically altered in human evolution. His team develops and shares infrastructure to support both research in and the clinical application of precision medicine.
Haussler received his Ph.D. in computer science from the University of Colorado at Boulder. He is a member of the National Academy of Engineering, National Academy of Sciences and the American Academy of Arts and Sciences and a fellow of the American Association for Artificial Intelligence. He has won a number of awards, including the 2015 Dan David Prize in the future category, 2011 Weldon Memorial prize for application of mathematics and statistics to biology, 2009 ASHG Curt Stern Award in Human Genetics, the 2008 Senior Scientist Accomplishment Award from the International Society for Computational Biology, the 2006 Dickson Prize for Science from Carnegie Mellon University, and the 2003 ACM/AAAI Allen Newell Award in Artificial Intelligence.