Prof. Dr. Alexander Boukhanovsky is the Chair of High Performance Computing (HPC) Department in ITMO University. In 2005, he defended his dissertation on Concurrent Software Statistical Measurements of Spatial-Temporal Fields. Since 2006 he has been working as a Professor of Information Systems and Head of the Parallel Software lab in ITMO University. In 2007 he created the eScience Research Institute where his team has created CLAVIRE (CLoud Applications VIRtual Environment).
In recent years he attracted several grants including mega grants of the Russian Federation Government, e.g. decree #220 “on measures to attract Leading Scientists in the Russian educational institution” and decree #218 “cooperation of Russian higher education institutions and organizations implementing complex projects of high-tech industry”.
His research interests are high-performance computing, computer modelling of complex systems, intelligent computational technologies, statistical analysis and synthesis of spatial-temporal fields, parallel and distributed computing, distributed environments for multidisciplinary researches, decision support systems and technologies, statistical analysis and simulation in marine sciences. He is the author of 230 publications (cited over 1000 times) and has successfully advised 23 PhD candidates.
Fellowship in Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NIAS) - INFORMATION SPREADING AND RESILIENCE IN CRIMINAL (DARK) NETWORKSGoogle Scholar
Alexander Boukhanovsky teaches the following courses:
- Probabilistic modelling (Master program: Supercomputing Technologies in Interdisciplinary Research)
- Probabilistic Modelling (Master’s Program: Big Data)
- Methods and Models for Multivariate Data Analysis (Master’s Program: Big Data)
- Probabilistic Modelling (Master’s Program: Computational Biomedicine)
- Probabilistic Modelling (Master’s Program: Urban Supercomputing) (as a part of Discrete and Probabilistic Models)
- Advances in Applied Mathematics and Computer Science
- Stochastic and discrete mathematical models