Bldg 32, Room S149
Greenbelt, MD 20771
Using remote sensing data in tracking infectious disease transmission such as malaria, dengue and influenza; role of weather in disease seasonality; frequency analysis; statistical and mathematical models
Dr. Soebiyanto received her B.S. (2002) and Ph.D. (2008) degrees in Systems and Control Engineering, and her M.E.M. (Masters of Engineering and Management, 2003) degree from Case Western Reserve University in Cleveland, Ohio. During her Ph.D. thesis, Dr. Soebiyanto developed a large-scale mathematical model of molecular interactions involved in cancer, and subsequently introduced a multilevel, hierarchical systems approach that can be used to guide the selection of biological experiments for the discovery of soft molecular targets. Dr. Soebiyanto worked as a mathematical modeler at Immunetrics (Pittsburgh, Pennsylvania), before joining GEST as a Research Associate in August 2008. She subsequently joined GESTAR in May 2011. Her current research is on using remotely-sensed environmental and climatic data in empirical and theoretical models to predict and facilitate the control of infectious disease transmission including vector-borne diseases. She is also studying the environmental signature on seasonal disease outbreaks. In the past few years she has developed statistical models to identify the climatic factors that are linked to seasonal influenza in more than 10 population centers around the world, ranging from cities in the temperate regions in the United States and Europe, to tropical and subtropical cities in the Asia, Central America and Africa. The identified relationships with climatic factors are then used to forecast influenza activity in each city. In 2015 Dr. Soebiyanto was selected as US nominee for the Asia-Pacific Economic Cooperation (APEC) Science Prize for Innovation, Research and Education (ASPIRE).