Phone: (865) 574-4966
Fax: (865) 241-6261
High Performance Geocomputation
PhD, State University of New York at Buffalo, Buffalo, NY (2004).
MS, Moscow State University, Moscow, USSR (1989).
2004 - Present, Oak Ridge National Laboratory
2000 - 2004, State University of New York at Buffalo, Buffalo, NY
1996 - 2000, Regional Science Institute, Sapporo, Japan
1990 - 1996, Russian Academy of Sciences, Moscow, RF
Awards, Honors, and Certifications
- October 2003: Student Paper Award, Fall Meeting of the Middle States Division, Association of American Geographers
- June 2003: Student Paper Award, University Consortium for Geographic Information Science Summer Assembly
- June 2001: Excellent Poster Award Presentation, University Consortium for Geographic Information Science Summer Assembly
- Geographic Information Science and Geospatial Ontology
- Interoperability Standards for Geographic Information Systems
- Parallel Computation Applications for Earth Sciences
- Geographic Visualization
- Environmental Modeling and Environmental Data Processing
Bhaduri, B., Shankar, M., Sorokine, A., and Ganguly, A. R. (2008). Spatio-temporal visualization for environmental decision support. In: Raffaele De Amicis, Radovan Stojanovic, Giuseppe Conti (Eds.), GeoVisual Analytics: Geographical Information Processing and Visual Analytics for Environmental Security, NATO Science for Peace and Security Series - C: Environmental Security. Springer. (in press)
Sorokine, A. (2007). Implementation of a parallel high-performance visualization technique in GRASS GIS. Computers & Geosciences, 33(5):685–695.
Sorokine, A., Bittner, T., and Renschler, C.S.(2006). Ontological investigation of a multiscale ecosystem classiﬁcation using the “National Hierarchical Framework of Ecological Units” as an example. GeoInformatica, 10(3):313–335.
Sorokine, A. (2003). Mereotopological integrity constraints in spatial databases. Middle States Geographer, 36:122–127.
Vinogradov B.V., Kulik, K.N., Sorokine, A. and Fedotov, P.B. (1999). Isodynamic mapping and long-term monitoring of desertiﬁcation and degradation of lands using nonlinear methods of modeling. Eurasian Soil Science, 32(4):449–458.