Mr. Sanjar Mirzakhalilov | Athletic Injuries Awards | Best Researcher Award

Mr. Sanjar Mirzakhalilov | Athletic Injuries Awards | Best Researcher Award

Mr. Sanjar Mirzakhalilov, Tashkent University of Information Technologies, Uzbekistan

Mirzakhalilov is an Associate Professor at Tashkent University of Information Technologies, where he has established a distinguished career in research and teaching. With a Master of Science in Information Technology, he specializes in developing algorithms and models for the intelligent analysis of athletes’ medical data, contributing over 40 scientific articles and theses to the field. His notable achievements include the publication of two textbooks and five methodological guides, demonstrating his commitment to advancing knowledge in sports medicine and data analysis. Proficient in network design, computer hardware, biotechnical systems, IoT technologies, and artificial intelligence, Mirzakhalilov aims to enhance athlete health monitoring through the integration of AI in sports medicine. His extensive experience in academia includes various roles, from Deputy Dean to Senior Lecturer, and his career reflects a dedication to fostering innovation and excellence in the application of technology in healthcare.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Mirzakhalilov is an exemplary candidate for the Best Researcher Award, holding the position of Associate Professor at Tashkent University of Information Technologies. His extensive experience in research and teaching, combined with his specialization in algorithms and models for intelligent analysis of athletes’ medical data, positions him as a leader in his field.

Education 🎓

  • Master of Science in Information Technology
    Tashkent University of Information Technologies, Tashkent (2010)
  • Bachelor’s Degree
    Tashkent University of Information Technologies (2004 – 2008)
  • Master’s Student
    Tashkent University of Information Technologies (2008 – 2010)

Work Experience 💼

  • Associate Professor
    Tashkent University of Information Technologies (09/2010 – Present)
  • Senior Lecturer
    Department of Information and Computer Technologies and Programming, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi (2021 – 2022)
  • Deputy Dean
    Joint Uzbek-Belarusian Faculty of Information Technologies, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi (2022 – 2023)
  • Deputy Dean
    Correspondence Department, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi (2023 – Present)
  • Senior Lecturer
    Department of Computer Systems, Tashkent University of Information Technologies (2017 – 2021)
  • Senior Lecturer
    Department of Computer Systems, Tashkent University of Information Technologies (2016 – 2017)
  • Deputy Dean
    Faculty of Computer Engineering, Tashkent University of Information Technologies (2014 – 2016)
  • Assistant of the Department
    Computer Systems, Tashkent University of Information Technologies (2010 – 2014)

Achievements 🏆

  • Scientific Contributions:
    • Over 40 scientific articles and theses published
    • 2 textbooks authored
    • 5 methodological guides published
  • Proficiency in:
    • Network design and construction
    • Computer hardware
    • Biotechnical systems hardware and software
    • Sports medicine
    • IoT technologies
    • Artificial intelligence

Career Goal 🎯

To advance the integration of AI in sports medicine for enhanced athlete health monitoring.

Publication Top Notes:

Accessible AI Diagnostics and Lightweight Brain Tumor Detection on Medical Edge Devices

Lightweight Deep Learning Framework for Accurate Detection of Sports-Related Bone Fractures

Dynamic Focus on Tumor Boundaries: A Lightweight U-Net for MRI Brain Tumor Segmentation

GAN-Based Novel Approach for Generating Synthetic Medical Tabular Data

A Multi-Scale Approach to Early Fire Detection in Smart Homes

Lightweight Super-Resolution Techniques in Medical Imaging: Bridging Quality and Computational Efficiency