As a computer scientist, Matt Might focuses on making software faster, safer and more secure. He has deep research expertise in automated, semantics-driven analysis of modern software systems and complex formal models. Additional research interests include domain-specific language design (especially for high-performance physical simulations) and novel techniques for efficient parsing of data in unrestricted (and potentially ambiguous) grammars. His work is funded by DARPA, NSF and the National Nuclear Security Administration. His interests in bioinformatics include Internet-driven case-finding for rare disease; systematizing delivery of care in genomic medicine; systems pharmacology; and in silico drug discovery. His true passion is accelerating the promise of genomic medicine for patients in need. In 2014, he was appointed one of six Presidential Scholars at the University of Utah. He received his Ph.D. in Computer Science from Georgia Tech in 2007. He regularly blogs at http://blog.might.net/ and tweets from @mattmight.
Prenatal diagnosis, December 30, 2016
Human mutation, August 27, 2015
Genetics in medicine : official journal of the American College of Medical Genetics, March 20, 2014