Ts. Dr. Muhammad Amir As’ari

Niche Area : Computer Vision, Artificial Intelligence, Image Processing.

Muhammad Amir Bin As’ari holds a PhD in Biomedical Engineering from the Universiti Teknologi Malaysia. His PhD’s work was in the field of assistive technology, computer vision and image procesing and his work focused on developing a novel 3D shape descriptors for recognizing the activities of daily living (ADLs) based on Kinect-like depth image. Amir pursued his master degree and bachelor degree at the Faculty of Electrical Eng, Universiti Teknologi Malaysia, majored in Electronic Engineering. His master degree and bachelor degree projects were also related to computer vision and image processing for security and surveillance. Currently, he is working on automated human action recognition based on wearable sensor and context-aware modality for assistive technology and sport technology.

Recent Projects

    1. Automated Vision Based Action Recognition In Badminton Using Deep Learning Approach
    2. Automated Vision Based Action Recognition In Field Hockey Using Deep Learning Approach
    3. Automated Activity Recognition In Badminton Using Inertial Sensor
    4. Automated Activity Recognition In Field Using Inertial Sensor
    5. Semen Analysis Using Deep Learning Approach


    1. Institut Sukan Negara
    2. Sekolah Sukan Tunku Mahkota Ismail

Selected Publications

    1. N. Ghazali, N. Sanat, and M. As’ ari, “Esports Analytics on PlayerUnknown’s Battlegrounds Player Placement Prediction using Machine Learning,” International Journal of Human and Technology Interaction (IJHaTI), vol. 5, no. 1, pp. 17-28, 2021.
    2. K. Rangasamy, M. A. As’ari, N. A. Rahmad, and N. F. Ghazali, “Hockey activity recognition using pre-trained deep learning model,” ICT Express, vol. 6, no. 3, pp. 170-174, 2020.
    3. K. Rangasamy, M. A. As’ ari, N. A. Rahmad, N. F. Ghazali, and S. Ismail, “Deep learning in sport video analysis: a review,” Telkomnika, vol. 18, no. 4, pp. 1926-1933, 2020.
    4. N. Rahmad, M. As’ari, K. Soeed, and I. Zulkapri, “Automated badminton smash recognition using convolutional neural network on the vision based data,” in IOP Conference Series: Materials Science and Engineering, 2020, vol. 884, no. 1: IOP Publishing, p. 012009.
    5. N. Shahar, N. Ghazali, M. As’Ari, and T. Swee, “Wearable Inertial Sensor for Human Activity Recognition in Field Hockey: Influence of Sensor Combination and Sensor Location,” in Journal of Physics: Conference Series, 2020, vol. 1529, no. 2: IOP Publishing, p. 022015.


Postgraduate Supervision

    • Keerthana A/P Rangasamy
    • Nur Anis Jasmin Binti Sufri
    • Norazman Bin Shahar
    • Syed Umer Saeed
    • Nur Azmina Binti Rahmad
    • Nurul Fathiah Binti Ghazali
    • Mispan Bin Mangon
    • Goh Voon Hueh

For More Info

Research Keyword : Deep Learning, Machine Learning, Activity Recognition, Sport Analytics

Lab : Intelligence Sport Technology Lab