Donald S. Burke, MD
Donald S. Burke, MD, is Dean of the Graduate School of Public Health, Director of the Center for Vaccine Research, and Associate Vice Chancellor for Global Health at the University of Pittsburgh. He is also first occupant of the UPMC-Jonas Salk Chair in Global Health. A native of Cleveland, Ohio, Dr. Burke received his B.A. from Western Reserve University and his M.D. from Harvard Medical School. He was an intern and resident in medicine at Boston City and Massachusetts General Hospitals and trained as a research fellow in infectious diseases at the Walter Reed Army Medical Center. He has studied prevention and control of infectious diseases of global concern, including HIV/AIDS, influenza, dengue, and emerging infectious diseases. He has lived six years in Thailand, worked extensively in Cameroon, and conducted field epidemiology studies in numerous other developing countries. Most recently he has led a transdisciplinary team that develops computational models and simulations of epidemic infectious diseases and uses these simulations to evaluate prevention and control strategies.
John J. Grefenstette, PhD
John J. Grefenstette, PhD, is the Director of the Public Health Dynamics Laboratory and Professor of Biostatistics in the Graduate School of Public Health at the University of Pittsburgh. He previously served as Professor and Chair of the Department of Bioinformatics and Computational Biology and Assistant Dean for the School of Computational Sciences at George Mason University, and as Head of the Machine Learning Section at the Navy Center for Applied Research in Artificial Intelligence at the U.S. Naval Research Laboratory. Dr. Grefenstette’s research activities span many areas on the boundary between computation and biology, including modeling and simulation of infectious diseases, public health databases, data mining, evolutionary algorithms, machine learning, computational models of biological networks, and high-performance computing applications to public health. His current major projects include the University of Pittsburgh’s National Center of Excellence for Models of Infectious Diseases Agent Study (MIDAS), funded by NIH/NIGMS, and the Vaccine Modeling Initiative, funded by the Bill and Melinda Gates Foundation. Dr. Grefenstette was the founding Associate Editor for the journal Evolutionary Computation, serves on the editorial board for the journal Adaptive Behavior and has been Associate Editor for the journal Machine Learning. Dr. Grefenstette received his BS in Mathematics and Philosophy from Carnegie Mellon University and his PhD in Computer Science from the University of Pittsburgh. In 2010, Dr. Grefenstette was honored with the Evolutionary Computation Pioneer Award from the IEEE Computational Intelligence Society.
Bryan A. Norman, PhD
Bryan A. Norman, PhD, is an Associate Professor of Industrial Engineering at the University of Pittsburgh. He received his Ph.D. degree in Industrial and Operations Engineering from the University of Michigan in 1995, where he was a National Science Foundation Fellowship holder, and has B.S.I.E. and M.S.I.E. degrees from the University of Oklahoma. His research interests primarily focus on the modeling of complex problems in manufacturing and production systems, applied optimization, and healthcare delivery and logistics. Specific areas relevant to the Vaccine Modeling Initiative include resource and personnel scheduling, facility design, material handling system design, supply chain network design and operations, inventory management, and healthcare delivery and logistics.His research has been funded by several sources including the National Science Foundation, the Gates Foundation and local industry. He has published his research in IIE Transactions, Naval Research Logistics, INFORMS Journal on Computing, the International Journal of Production Research, the European Journal of Operational Research, the Annals of Operations Research and Computers and Industrial Engineering. He is a member of IIE and INFORMS.
Jayant Rajgopal, PhD
Jayant Rajgopal, PhD, holds a Ph.D. in Industrial and Management Engineering from the University of Iowa, and has been on the faculty of the Department of Industrial Engineering at the University of Pittsburgh since 1986. His areas of interest include optimization, analysis of operations and supply chains, health systems modeling, and RFID applications; he has taught, conducted sponsored research, published papers and consulted in all these areas. He is a senior member of the Institute of Industrial Engineers, and the Institute for Operations Research and the Management Sciences, and is a licensed professional engineer in the state of Pennsylvania.
Wilbert van Panhuis, MD, PhD
Wilbert van Panhuis, MD, PhD, is an assistant professor in the Department of Epidemiology and a faculty member of the Public Health Dynamics Laboratory, University of Pittsburgh Graduate School of Public Health. Dr. Van Panhuis studied medicine at the Vrije Universiteit Medical Center in Amsterdam after which he worked as a research fellow at the Center for Research on the Epidemiology of Disasters in Brussels. He completed an internship at the WHO Western Pacific Regional Office in Manila where he worked on dengue surveillance in the Mekong Region. He received his PhD from the Department of International Health, Johns Hopkins Bloomberg School of Public Health. Dr. Van Panhuis is an infectious disease epidemiologist specializing in (inter)national disease surveillance systems, vector-borne and vaccine preventable diseases and global cooperation for disease data sharing and disease control. He is the lead scientist of the Tycho project which aims to provide open access to newly digitized, standardized US weekly disease surveillance data in a dynamic online user environment. He is also working with colleagues, students and partner organizations in the United States, Southeast Asia and Latin America to assess disease surveillance systems and to use high resolution surveillance data for studies on the spatiotemporal spread of infectious diseases. Dr. Van Panhuis is particularly interested in time series and geospatial methods to study the influence of population density and urbanization on disease transmission, especially across country borders. He works on technology and policy solutions to advance the use of high resolution disease data for dynamic computational modeling in support of decision making, bridging the gap between data, analytics, and policy making. He plans to establish a central online access point to integrated, standardized country disease surveillance data in the public domain to create new opportunities for technological innovation, scientific advancement, and more effective investments in global health.