Ph.D. The Flinders University of South Australia, 1979
"Leading initiatives to encourage and facilitate the use of “big data” in large-scale research across the scientific and technological disciplines."
Philip E. Bourne, Dean of the School of Data Science
Philip E. Bourne is the Founding Dean of the School of Data Science and Professor of Biomedical Engineering.
From 2014-2017, Phil was the Associate Director for Data Science at the National Institutes of Health. In this role he led the Big Data to Knowledge Program, coordinating access to and analyzing biomedical research from across the globe and making it available to scientists and researchers. While there, he was also responsible for governance and strategic planning activities for data and knowledge management, and established multiple trainings in data science. He has done exceptional work to make biomedical research accessible, as well as to advance the field of data science.
Prior to his time at the NIH, Phil spent 20 years on the faculty at the University of California-San Diego, eventually becoming Associate Vice Chancellor of Innovation and Industrial Alliances. He is a highly respected and oft-cited scholar who brings a wealth of experience to UVA.
College of Fellows, American Institute of Medical and Biological Engineering2018
Fellow of the American Association for the Advancement of Science (Pharmaceutical Sciences)2011
Fellow of the International Society for Computational Biology2011
Microsoft's Jim Gray e-Science award2010
Benjamin Franklin Award2009
Multiscale Modeling Using Data Science Techniques
Early Stage Drug Discovery and Drug Repurposing
Early Stage Drug Methods and Tools for Macromolecular Structure Analysis
The University of Virginia's School of Data Science will enable research collaborations across fields to solve real-world problems, provide students with interdisciplinary opportunities to learn technical and practical skills and go on to create positive impacts in a variety of industries and...
T.A. Koleck, C. Dreisbach, P.E. Bourne & S. Bakken 2019 A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data. Int. J. of Medical Informatics 125:37-46
C. Mura, E.J Draizen & P.E. Bourne 2018 Structural Biology Meets Data Science: Does Anything Change? Curr. Op. in Struct. Biol., 52: 95-102
P.E. Bourne 2017 Life is 3-dimensional and it begins with Molecules PLOS Biology 15(3): e2002041
L. Xie, E.J. Draizen & P.E. Bourne 2017 Harnessing Big Data for Systems Pharmacology. Annual Review of Pharmacology and Toxicology, 57: 245-262
J.M. Berg, N. Bhalla, P.E. Bourne, et al. 2016 Preprints for the Life Sciences. Science, 352(6288) 899-901
P.E. Bourne, J.R. Lorsch & E.D. Green 2015 Perspective: Sustaining the Big-Data Ecosystem. Nature 527 S16-S17