Umair Sajid Hashmi

National University of Sciences and Technology, Bahria University

Papers

Total Citations

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About

Umair Sajid Hashmi is a forward-looking researcher at the intersection of wireless communications and autonomous systems. His primary research areas include demand-driven network optimization for 6G and beyond, as well as path planning algorithms for mobile robotics. His most impactful work, "D-RAN: A DRL-Based Demand-Driven Elastic User-Centric RAN Optimization for 6G & Beyond" (2022, 17 citations), proposes a novel deep reinforcement learning framework to redesign cellular architecture. This work addresses the critical need for elastic, user-centric networks capable of supporting highly heterogeneous application requirements in next-generation systems. Hashmi’s earlier research, "Performance Analysis of Different Optimal Path Planning Bug Algorithms on a Client Server Based Mobile Surveillance UGV" (2013, 7 citations), explores efficiency parameters such as distance and time for unmanned ground vehicles in surveillance and military contexts. By bridging intelligent network design with autonomous navigation, Hashmi contributes to the foundational technologies that will enable seamless connectivity and adaptive robotic systems. His work is particularly relevant for students and researchers interested in the convergence of AI-driven network optimization and real-world autonomous applications.