Talk: Philip Bourne on Opinion Mining, Machine Learning and Big Data, 10am Tue 5/5, UMBC
Spring 2015 IS Distinguished Lecture
Department of Information Systems
Opinion Mining, Machine Learning and Big Data
Dr. Philip Bourne
Associate Director for Data Science
The National Institutes of Health
10:00am Tuesday, 5 May 2015, ITE 456, UMBC
Philip E. Bourne is the Associate Director for Data Science at the National Institutes of Health. Formally he was Associate Vice Chancellor for Innovation and Industry Alliances, a Professor in the Department of Pharmacology and Skaggs School of Pharmacy and Pharmaceutical Sciences at the University of California San Diego, Associate Director of the RCSB Protein Data Bank and an Adjunct Professor at the Sanford Burnham Institute.
Bourne's professional interests focus on service and research. He serves the national biomedical community through contributing ways to maximize the value (and hence accessibility) of scientific data. His research focuses on relevant biological and educational outcomes derived from computation and scholarly communication. This implies algorithms, text mining, machine learning, metalanguages, biological databases, and visualization applied to problems in systems pharmacology, evolution, cell signaling, apoptosis, immunology and scientific dissemination. He has published over 300 papers and five books, one of which sold over 150,000 copies.
Bourne is a Past President of the International Society for Computational Biology, an elected fellow of the American Association for the Advancement of Science, the International Society for Computational Biology and the American Medical Informatics Association. His awards include: the Jim Gray eScience Award (2010), the Benjamin Franklin Award (2009), the Flinders University Convocation Medal for Outstanding Achievement (2004), the Sun Microsystems Convergence Award (2002) and the CONNECT Award for new inventions (1996 and 1997).
Posted: April 29, 2015, 2:10 PM