Arindam Khan

University of Applied Sciences and Arts of Southern Switzerland

Papers

Total Citations

243

H-Index

About

Arindam Khan is a leading researcher in approximation algorithms, with a primary focus on combinatorial optimization and packing problems. His most influential work centers on multidimensional bin packing, a fundamental challenge in computer science with applications in cloud computing, logistics, and resource allocation. Khan’s comprehensive survey on approximation and online algorithms for multidimensional bin packing (2017), which has garnered 233 citations, serves as a definitive resource for researchers in the field. In this work, he systematically categorizes and analyzes the state-of-the-art techniques, bridging gaps between theoretical guarantees and practical implementations. His earlier foundational paper (2015) further advanced the understanding of approximation algorithms for these complex problems, offering novel insights into packing items in multiple dimensions. Khan’s contributions have significantly shaped the algorithmic landscape, providing efficient solutions for resource optimization. His research not only deepens theoretical knowledge but also drives practical innovations in data center efficiency and supply chain management. With a citation count exceeding 240, Khan’s work continues to inspire new generations of algorithm designers tackling real-world packing challenges.