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Yulia A. Orlova

Name: Yulia A. Orlova

Gender: Female

Birthday: November, 17 1984

Address: Volgograd, Russia

Ethnicity.: Russian

Teaching Experience: 17 years

Ph.D. Thesis Automation of semantic analysis of the technical request. Modern information technologies as a means of increasing the effectiveness of training future managers in higher education institutions of physical culture

Prof. Ph.D. Models and methods of information support of communications of people with disabilities

? Education

  • 2016: Dr.Tech.Sc. (Systems theory, information processing and control), Belgorod State University
  • 2014: PostDoc (Systems theory, information processing and control), Volgograd State Technical University
  • 2009: PhD (Candidate of Pedagogical Science), Volgograd State Technical University
  • 2008: PhD (Candidate of Technical Science), Volgograd State Technical University
  • 2007: Master of Science in Computer Science, Volgograd State Technical University
  • 2005- 2007: Manager, specialty “Management of organization”, Volgograd State Technical University
  • 2005: Bachelor of Science in Information Systems, Volgograd State Technical University; Bachelor of Science in Economics, Volgograd State Technical University;

?Teaching/Supervising Experience

  • System analysis
  • Methods of fuzzy information analysis
  • Data mining and visualization
  • Compiler Design

?Working Experience

  • July, 2017 – present

    Head Of Software Engineering Department, Volgograd State Technical University, Volgograd, Russia

  • September, 2008 – Jun, 2017

    Professor, Assistant Professor, Research Scientist, Volgograd State Technical University, Volgograd, Russia

?Research

Project Lead:

  • RFBR grant 20-07-00502 (2020-2022): Development of technology and tools of preventive interactive patient support
  • RFBR grant 20-37-90004 (2020-2022): Development of models, methods and software for generating genre musical compositions based on a person’s emotional state
  • RFBR grant 19-47-340003 (2019-2020): Development of models, methods and software for generating genre musical compositions based on a person’s emotional state

Team Member:

  • RSF grant 18-78-10047 (2018-2022): The development of scientific and methodical approaches to assessment of efficiency of national systems of basic research funding
  • RFBR grant 19-47-343001 (2019-2020): Development of methods and means of adapting the interface of electronic resources
  • RFBR grant 19-47-340009 (2019-2021): Development of methods and means of optimization using video courses and a neural interface

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