Dr. Mohtashim Baqar is a researcher and academic with extensive experience in the domains of computer vision, artificial intelligence, and networked systems. He holds a PhD in Computing from Sunway University, Malaysia, where his research focused on perceptual image quality assessment and deep learning-driven reconstruction frameworks. With a background spanning both academia and industry, Dr. Baqar has contributed to educational institutions such as Iqra University, Melbourne Institute of Technology, and CQUniversity, and has worked as a Computer Vision Engineer in industry. His interdisciplinary expertise supports a deep understanding of emerging technologies and their real-world applications. Dr. Baqar’s academic and research interests include: Computer Networks, Big Data Analytics, Cybersecurity, Artificial Intelligence, Machine Learning, Computer Programming (Basic and Advanced), Research Methods and Project Management, Information Security, and Blockchain. He is actively involved in research publication, peer review, and professional development, and holds certifications in TensorFlow, Computer Vision, and data science. Dr. Baqar is a member of IEEE and PEC.

1. Mohtashim Baqar, Sian Lun Lau and Mansoor Ebrahim, “FR-IQA - Permutation Entropy Deviation Index”, 2019 IEEE International Conference on Visual Communications and Image Processing (VCIP), December 1-4, 2019, Sydney, Australia.

2. Mohtashim Baqar, Azfar Ghani, Azeem Aftab, Saira Arbab and Sajid Yasin, “Deep Belief Networks for Iris Recognition Based on Contour Detection”, Proceedings of 10th IEEE International Conference on Open Systems and Technologies, Lahore, Pakistan, December 2016.

3. Mohtashim Baqar, Sian Lun Lau and Mansoor Ebrahim, “GMSD-based Perceptually Motivated Non-local Means Filter for Image Denoising”, IEEE International Symposium on Haptic Audio-Visual Environments & Games, October 3 - 4, 2019, Kuala Lumpur, Malaysia.