Syed Asad Ullah
Lecturer (On Study Leave)
Department of Electronic Engineering , Faculty of ICT

syed.asad@buitms.edu.pk

Qualification

Ph.D. (2025)
Electrical Engineering
National University of Sciences & Technology (NUST), Pakistan
Master's (2017)
Electrical Engineering
National University of Sciences & Technology (NUST), Pakistan
Bachelor's (2013)
Electronic Engineering
Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS), Pakistan

Teaching Courses

  • Signals & Systems
  • Data Communication & Networking
  • Mobile Communications
  • Machine Learning
  • Convex Optimization
  • Probability Theory
  • Computer Technology
  • Advanced Wireless Communication
  • Mathematical Methods for AI

Teaching Method

  • Collaborative Learning
  • Spaced Learning
  • Self-learning
  • Gamification
  • Visual, Audio, & Kinesthetic Teaching
  • Expeditionary Learning
  • Inquiry-Based Learning

Research Interest

  • Machine Learning for IoT
  • Network Optimization
  • AI for Wireless Communications
  • DRL-based Resource Optimization in IoT Networks

Awards & Achivements

  • Best Faculty Award
    2019
  • Best Faculty Award
    2018
Dr. Syed Asad Ullah earned his PhD degree in Electrical Engineering from NUST, Islamabad, Pakistan. He is serving as a lecturer at Baluchistan University of Information Technology Engineering and Management Sciences (BUITEMS), Quetta, where his exceptional contributions earned him the 'Best Faculty Member' award twice. Dr. Asad specializes in deep reinforcement learning (DRL) for sustainable and intelligent resource optimization in next-generation wireless communication systems. His work focuses on integrating DRL with enabling technologies such as mobile edge computing (MEC), energy harvesting, non-orthogonal multiple access (NOMA), backscatter communication (BackCom) and reconfigurable intelligent surfaces (RIS) to improve spectral and energy efficiency in IoT, vehicular, and non-terrestrial networks (NTNs). He has published in high-impact IEEE journals and flagship conferences, including IEEE Communications Surveys & Tutorials, IEEE Internet of Things Journal, and IEEE Network.

Publications

DRL-Driven Dual-Stage Resource Optimization Strategy for Efficient Computational Offloading in MEC-Enabled Vehicular Networks
Mehwish Bibi, Syed Asad Ullah, Haejoon Jung, Syed Ali Hassan (2025) IEEE Transactions on Vehicular Technology vol. - no. - pp. -
Convergence of MEC and DRL in Non-Terrestrial Wireless Networks: Key Innovations, Challenges, and Future Pathways
Syed Asad Ullah, Syed Ali Hassan, Hatem Abou-Zeid, Hassaan Khaliq Qureshi, Haejoon Jung, Aamir Mahmood, Mikael Gidlund, Muhammad Ali Imran, Ekram Hossain (2025) IEEE Communications Surveys & Tutorials vol. - no. - pp. -
Towards Intelligent and Sustainable IoT: A DRL Approach for Backscatter-Based Communication Under QoS Constraints
Hafiz Muhammad Ali Zeeshan, Syed Asad Ullah, Muhammad Sohaib J Solaija, Muhammad Ali Jamshed, Mohammad Mahdi Mojahedian, Haejoon Jung, Syed Ali Hassan (2025) IEEE Open Journal of the Communications Society vol. - no. - pp. -
Multi-Agent Deep Reinforcement Learning for Energy Efficient RIS-assisted CoMP-NOMA Networks
Ahmad Faisal Mirza, Fatima Binte Tanveer, Muhammad Umer, Syed Asad Ullah, Haejoon Jung, Syed Ali Hassan (2025) 2025 IEEE International Conference on Communications Workshops (ICC Workshops) vol. - no. - pp. 1809-1814
AI-driven Computation Offloading in MEC-enabled Vehicular Networks: A Dual-Stage DRL Framework
Syed Zain Abbas, Syed Asad Ullah, Mehwish Bibi, Haejoon Jung, Hatem Abou Zeid, Aryan Kaushik, Syed Ali Hassan (2025) 2025 IEEE International Conference on Communications Workshops (ICC Workshops) vol. - no. - pp. 554-559
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Work Experience

July 2016 to Date
Lecturer at Electronic Engineering
Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS)
September 2025 to October 2025
Visiting Researcher at Electronics and Communication Engineering
Kyung Hee University (KUH)