Junaid Shuja

Junaid Shuja is a researcher with significant contributions to Mobile Edge Computing, Cloud Environments, and IoT Systems. Collaborating with scholars like Kashif Bilal, Abdullah Gani, and Ehzaz Mustafa, his work spans computation offloading, resource allocation, and security frameworks.

Research Highlights
• 2017: Analysis of Vector Code Offloading in Heterogeneous Architectures
• 2021: Survey on Machine Learning for Edge Caching
• 2023: Reinforcement Learning for Computation Offloading in Vehicular Networks
• 2024: Blockchain Applications in Land Lease Systems and Employee Transfers
• 2025: Deep Reinforcement Learning for Resource Optimization

His recent work focuses on Deep Learning and Blockchain for latency-sensitive applications in IoT and vehicular networks, published in IEEE Access, Cluster Computing, and Telecommunication Systems. Key co-authors include Faisal Rehman, Abdallah Namoun, and Muhammad Bilal.