Junaid Khan

Institute of Business Administration Karachi

Papers

Total Citations

H-Index

About

Junaid Khan is a mathematician whose work lies at the intersection of graph theory, metric dimension, and combinatorial optimization. His research focuses on resolving partitions and resolving sets—concepts essential for applications in robot navigation, network design, and optimization problems like the mastermind game and coin weighing. Khan’s most cited paper, “Sharp bounds for partition dimension of generalized Möbius ladders” (2018, 15 citations), provides exact bounds for the partition dimension of these complex graph structures, a nontrivial problem in graphic metric spaces. This contribution is notable for its precision and applicability to real-world systems requiring efficient location and identification. Khan’s work advances the theoretical understanding of metric dimension, offering tools that bridge abstract graph theory and practical challenges in networking and robotics. His research continues to inspire further exploration into resolving parameters, making him a valuable voice in discrete mathematics and its interdisciplinary applications.