Victoria Rayskin received her Ph.D. from the University of California at Berkeley, in Mathematics, focusing on Dynamical Systems. During the years of her employment in academia and industry (UCLA, Tufts University, Deloitte LLP, Tokyo Electron, Inc.) she has been using statistics, machine learning, dynamical systems and analysis.

Jointly with Genrich Belitskii, Rayskin developed a new approach for smooth localization of maps on Banach spaces. They applied this technique for smooth linearization in a neighborhood of a fixed point—a convenient simplification of complex dynamical systems. Together with Boris Hasselblatt and Misha Guysinsky, Rayskin proved existence of linearization in lower classes of smoothness for maps with resonances, and later obtained some generalizations for Banach spaces (with Belitskii).

Tackling problems in signal processing, Rayskin developed a new approach for the study of time series, applying the ideas of dynamical systems theory to the data analysis and forecasting. The technique developed in her projects helped to design models for prediction of volume of users interacting through popular Internet platforms (Wikipedia and real estate rental platforms), and for COVID-19 cases prediction in multiple countries.

Recent Projects and Research

  • Novel method for multivariate time series analysis. Prediction of the number of COVID-19 cases and the study of its long-term dynamics.
  • Smooth localization of maps on Linear Topological Spaces.
  • Whitney and Seeley type of Results for maps' extension on some Banach spaces.

Recent Publications

  • G. Belitskii, V. Rayskin, "A New Method of Extension of Local Maps of Banach Spaces. Applications and Examples," Contemporary Mathematics, v.733, AMS (2019)
  • V. Rayskin, "Users' traffic on two-sided Internet platforms. Qualitative dynamics," American Institute of Physics Conference Proceedings, 2164, 120012 (2019)
  • G. Belitskii, V. Rayskin, "New Method of Smooth Extension of Local Maps on Linear Topological Spaces. Applications and Examples," Progress on Difference Equations and Discrete Dynamical Systems. Springer Proceedings in Mathematics & Statistics (2019)
  • V. Rayskin, "Modeling the Dynamics of the Internet Platform Users' Volume," SIMIODE (2018)
  • V. Rayskin, "Users' dynamics on digital platforms," Mathematics and Computers in Simulation, 142 (2017)
  • V. Rayskin, "Dynamics of Two-Sided Markets," Review of Marketing Science, vol. 14, issue 1 (2016)
    • Professional Honors and Awards

      • Certificate of Appreciation for the SCUDEM LITE 2020 competition judging.
      • DoD/ARO award #W911NF-19-1-0399 (PI role).
      • NSF-CBMS travel funding for the conference "Fitting Smooth Functions to Data,"
      • NEAM2019 conference travel award
      • NSF/DEMARC travel funding for DEMARC Workshop
      • DEMARC publication reward
      • AMS travel grant for attendance at the International Congress of Mathematicians
      • Grant for participation in the 5th Annual NIGMS Workshop on Statistical Genetics and Genomics
      • Isaac Newton Institute Grant for participation in the workshop on Relaxation Dynamics of Macroscopic Systems
      • NSF travel grant DMS 0218051
      • SFI Grant, "Modeling & Simulating Biocomplexity," Workshop
      • AMS Grant for attendance at the 1999 Summer Research Institute on Smooth Ergodic Theory and Applications
      • AWM Grant for attendance at O.Taussky Todd Celebration of Careers in Mathematics for Women
      • AMS Grant for attendance at the International Congress of Mathematicians in Berlin, Germany

      Courses Taught at NYIT

      • Math 170 Calculus I

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