KHAYRETDINOVA Guzel

 

  • Thèmes de recherche/Research topics:
    Modélisation math et simulation numérique, applications / Math modelling and numerical simulation, biomedical applications, shape optimization
  • June 2021/2024 Phd  -  Advisors : Christian Gout (INSA Rouen, France) & Sergei Kuksenko : Mathematical modelling and numerical simulation for biomedical applications : from the process of drug delivery to image segmentation process on medical images.
  • March 2023 : 3D printing works >>>
  • 2019/20 : Survey in Image segmentation under geometrical constraints for medical applications (with Christian Gout)
  • Soutenance de thèse : prévue fin 2024.

 

 
      •  Articles (international journals)
        • G. Khayretdinova, D. Apprato, C. Gout,  A level set based model for image segmentation under geometric constraints and data approximation, Journal of Imaging 10-1 (2), 19p., 2024. [Journal of Imaging, Q2: Computer graphics and CAGD, radiology, nuclear medicine and imaging, computer vision and pattern recognition, electrical and electronic engineering in 22/23].
        • G. Khayretdinova, T. Chaumont-Frelet, C. Gout, S. Kuksenko, Image segmentation with a priori conditions: applications to medical and geophysical imaging, Math. Comput. Appl. 27(2), 26, 2022. [Math. Comput. Appl. : Q2 in engineering in 2020-unranked since property transfer]
      • Conférences and  communications
        • May 22-26, 2023 : Conference SMAI 2023, Wind velocity field and oceanic surface currents approximation and visualization from sparse data, Guadeloupe, France. 
        • Image segmentation under constraints : theory and applications to medical images, G. Khayretdinova, November 17, 2022,  @Conference : 6èmes Journées  rouennaises MNSN" : Modélisation Mathématique et Simulation Numérique pour le traitement d'image, l'énergie, le développement durable et la morphodynamique côtière, Rouen France.
        • Image segmentation with a priori conditions: applications to medical and geophysical imaging, G. Khayretdinova, Workshop "Intelligence Artificielle - Applications et défis mathématiques", Cycle de journées nationales [AMIES, INSMI], "Intelligence Artificielle & Entreprises  - Applications et défis mathématiques", INSA Rouen, september 30, 2021.
        • A survey of image segmentation under geometrical constraintes in medical image, G. Khayretdinova, Modelling and numerical simulation workshop @ INSA, Nov. 21-22, 2019.
        • Traffic Sign Classification with Tensorflow, D. Lechshinskiy, M. Povzun, G. Khayretdinova, I. Shlotgauer, Day on Approximation de données : applications en imagerie et data science - GM5, LMI- INSA Rouen,  march 3, 2019.
        • Image processing : edge detection, D. Lechshinskiy, M. Povzun, G. Khayretdinova, I. Shlotgauer, Day on Approximation de données : applications en imagerie et data science - GM5, LMI-INSA Rouen,  march 3, 2019.
        • Scientific conference of students of mechanics and mathematics department, TSU Nov. 24-29, 2017, Tomsk.
        • Scientific conference of students of mechanics and mathematics department, TSU April 25-30, 2017, Tomsk.
        • Youth scientific conference "All aspects of mathematics and mechanics", TSU 20.04.16 - 25.04.16, Tomsk.
        • Siberian conference on parallel and high performance computing, TSU 25.10.15 - 28.10.15, Tomsk.
      • Grant/Funding
        • 2023: 4,5 months + 2 months (INSA Rouen, INTERWIND)
        • October-December 2021 (3 months project funding from INSA Rouen) : image segmentation, variational approach, deep learning approaches.
        • Since 2021 : Scholarship (TUSUR)
      • Administration
      • Master's thesis
        • Space of continuously differentiable functions, G. Khayretdinova, 37 p., Université de Rouen, 2019.
      • Formation
        • Université de Rouen, France (2018-2019)
          Master in Mathematics : Modélisation et Analyse Mathématique (Mathematical Modelling and Analysis)
          Education fields (direction): Mathematical modeling (double degree programme)
          Degree: Master of mathematics
          Master thesis advisors : T. Khmyleva (Tomsk) and A. Bouziad (Rouen).
        • Tomsk State University (2017-2019)
          Faculty of Mechanics and Mathematics
          Education fields (direction): Mathematical analysis and modeling (double degree programme)
          Degree: Master of mathematics
        • Tomsk State University (2013-2017)
          Faculty of Mechanics and Mathematics
          Education fields (direction): Mathematics and computer sciences
        • Degree: Bachelor of mathematics
          Graduation qualification thesis (Bachelor’s thesis) themed “Spaces of continuously-differentiable functions”

 

Vector field approximation and visualization (basic tests)

(wind in Normandie, and rising tide effect in Rouen)

Other visualization [Eolin framework] >>>