Irina Kukuyeva, Ph.D.

Work Experience
Data Science Consultant with over 10 years of experience developing analytics solutions for companies in IoT, healthcare, market research, online advertising and remote sensing and working as a liaison between the technical and business/clinical stakeholders to solve business problems.

   University of California, Los Angeles
Ph.D., M.S. in Statistics    
       B.A. and S. in Statistics and Economics, Minor in Mathematics
  • PhD thesis proposed a new dimension reduction technique called Tensor Independent Component Analysis (TICA) that reduces the volume and noise in high dimensional data sets (which data sets are best represented by 3D, 4D, etc. objects, not matrices). One application of the methodology developed is remote sensing, where observations are described by longitude, latitude and wavelength. We focus on analyzing remotely sensed multispectral images of the White Oval on Jupiter (captured by the Hubble Space Telescope and the Infrared Telescope Facility). TICA uncovers similarities in temperature gradients between the White Oval and the Great Red Spot.
  • Spatial statistics: Project 1 (2008), Project 2 (2009)
  • Nonparameteric statistics and remote sensing: Project (2009), PhD thesis (2012)