Dr. M. Shahwar Asad

Assistant Professor

muhammad.shahwar@cust.edu.pk

+92-51-111-555-666

PROFILE SUMMARY

Dr. M. Shahwar Asad earned his Doctorate (PhD) in Software Engineering from Qingdao University, China. His doctoral research focused on AI-driven physical layer security, specifically developing Deep Reinforcement Learning (DRL) techniques for Intelligent Reflecting Surface (IRS)-assisted Terahertz communication in 6G networks. His research interests include Artificial Intelligence for Wireless Communications, Physical Layer Security, 6G Networks, and the Internet of Things (IoT). He has a strong publication record in high-impact journals such as IEEE Access and the IEEE Internet of Things Journal. Dr. M. Shahwar has supervised multiple master’s students and has been actively involved in academia, serving as a Teaching Assistant for various computer science courses during his master’s program. As a dedicated researcher and educator, Dr. M. Shahwar aims to advance the frontiers of secure and intelligent communication systems for next-generation networks while mentoring future engineers and computer scientists.

QUALIFICATION
PhD	Software Engineering	Qingdao University, China	2025
MS	Computer Engineering	Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Swabi	2021

TEACHING EXPERIENCE
Assistant Professor	Capital University of Science and Technology (CUST), Islamabad.	Since 2025

RESEARCH AREAS / INTERESTS
1.	Wireless Communications
2.	Physical Layer Security
3.	Intelligent Reflecting Surface (IRS)

Sr.	JOURNAL PUBLICATIONS	Year
1	M. Ahmed, T. Hussain, M. Shahwar, F. Khan, M. Sheraz, W. U. Khan, T. C. Chuah, and I. E. Lee, “Intelligent reflecting surface backscatter-enabled physical layer security enhancement via deep reinforcement learning,” PeerJ Computer Science, vol. 11, p. e2902, 2025	2025
2	M. Shahwar, M. Ahmed, T. Hussain, M. Sheraz, W. U. Khan, and T. C. Chuah, “Secure THz communication in 6G: A two-stage DRL approach for IRS-assisted NOMA,” IEEE Access, vol. 13, pp. 85 294–85 306, 2025	2025
3	M. Shahwar, M. Ahmed, T. Hussain, S. Ahmad, W. U. Khan, M. Sheraz, and T. C. Chuah, “Terahertz-based IRS-assisted secure symbiotic radio communication: A DRL approach,” IEEE Access, vol. 13, pp. 24 014–24 027, 2025	2025
4	M. Ahmed, M. Shahwar, F. Khan, W. U. Khan, A. Ihsan, U. S. Khan, F. Xu, and S. Chatzinotas, “NOMA-based backscatter communications: Fundamentals, applications, and advancements,” IEEE Internet of Things Journal, vol. 11, no. 11, pp. 19 303–19 327, 2024	2024
5	T. Hussain, M. Shahwar, S. Z. U. Abdin, Z. Zaheen, N. Jan, and M. Shoaib, “IRS integrated UAV communication to enhance physical layer security: A deep reinforcement learning approach,” The Asian Bulletin of Big Data Management, vol. 4, no. 02, pp. 135–149,2024	2024
6	M. Awais, Z. Zaheen, Z. Fatima, M. Shahwar, N. Jan, and S. Ali, “Spatiotemporal drought assessment in Ningxia Autonomous Region: A machine learning and remote sensing approach,” Asian Bull. Big Data Manage, vol. 4, no. 2, pp. 119–134, 2024	2024
7	G. Abbas, Z. H. Abbas, Z. Ali, M. S. Asad, U. Ghosh, and M. Bilal, “Smart stochastic routing for 6G-enabled massive internet of things,” Computer Communications, vol. 180, pp. 284–294, 2021	2021

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Dr. M. Shahwar Asad

PROFILE SUMMARY

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