Vladimir Zadorozhny

  • Professor

Vladimir Zadorozhny is a Professor in DINS and also a Core Faculty Member at the University of Pittsburgh Biomedical Informatics Training Program and Adjunct Professor at Faculty of Engineering and Science of the University of Agder. He received his Ph.D. in 1993 from the Institute for Problems of Informatics, Russian Academy of Sciences in Moscow. Before coming to USA he was a Principal Research Scientist in the Institute of System Programming, Russian Academy of Sciences. Since 1998 he worked as a Research Associate in the University of Maryland Institute for Advanced Computer Studies at College Park. He joined University of Pittsburgh in 2001. His research interests include information integration, data fusion, complex adaptive systems and crowdsourcing, query optimization in resource-constrained distributed environments, sensor data management, and scalable architectures for wide-area environments with heterogeneous information servers. His research has been supported by NSF, EU and Norwegian Research Council. Vladimir is a recipient of Fulbright Scholarship for 2014-2015.  He has received several best paper awards and has chaired and served on program committees of multiple Database and Distributed Computing Conferences and Workshops.  His specific interests within CAIR are related to application of scalable data fusion methods to enable efficient data mining and machine learning in complex domains, such as large-scale monitoring of social dynamics and reliability assessment in biomedical data.

Institution of Highest Degree

  • Russian Academy of Sciences, Ph.D.

Representative Publications

D Zhang, VI Zadorozhny, "Fake News Detection Based on Subjective Opinions," European Conference on Advances in Databases and Information Systems, 108-121, 2020.

J Xu, V Zadorozhny, J Grant, "A-Cure: An accurate information reconstruction from inaccurate data sources," Information Systems (91), 2020.

F Firoozi, VI Zadorozhny, FY Li, "Subjective logic-based in-network data processing for trust management in collocated and distributed wireless sensor networks," IEEE Sensors Journal 18 (15), 6446-6460, 2018

Research Interests

Information integration, data fusion
Complex adaptive systems and crowdsourcing
Query optimization in resource-constrained distributed environments
Sensor data management
Scalable architectures for wide-area environments with heterogeneous information servers