ICCK

Md. Najmul Hossain

Department of Electrical, Electronic and Communication Engineering, Pabna University of Science and Technology, Pabna 6600, Bangladesh

Section 01

Academic Profile

Md. Najmul Hossain (Senior Member, IEEE) was born in Rajshahi, Bangladesh, in 1984. He received the B.Sc. and M.Sc. degrees in Applied Physics and Electronic Engineering (currently named Electrical and Electronic Engineering) from the University of Rajshahi, Rajshahi, in 2007 and 2008, respectively, and the Ph.D. degree in advanced wireless communication systems from the Graduate School of Science and Engineering, Saitama University, Saitama, Japan, in 2020. He is currently working as an Associate Professor with the Department of Electrical, Electronic and Communication Engineering, Pabna University of Science and Technology, Pabna, Bangladesh. His current research interests include computer vision, antenna and wave propagation, advanced wireless communications, and corresponding signal processing, especially for OFDM, OTFS, OCDM, MIMO, and future-generation wireless communication networks. In 2010, he was awarded a Gold Medal for his excellent academic performance. He is a member of the IEEE Communications Society (ComSoc). He is collaboratively conducting research with several renowned professors, such as Prof. Shimamura, Saitama University, Japan; Prof. Shin, University of Aizu, Japan; Prof. Heung-Gyoon Ryu, Chungbuk National University, South Korea; Prof. Raad, University of Wollongong, Wollongong, Australia; and Prof. Nisar, Prince Sattam bin Abdulaziz University, Saudi Arabia. He has served as a Reviewer of several SCI/SCIE/Scopus journals and international conferences. In addition, he served as an Editor for the Journal of Engineering Advancements.

Section 02

Editorial Roles

This user currently does not serve as an editor for any ICCK journals.

Section 03

ICCK Publications

Open Access | Research Article | 13 January 2026 | Cited: Crossref logo  2 , Scopus 2
Dispersion-Compensating Method for High-Capacity Fiber-Optic Communication System Using Machine Learning Optimization
ICCK Transactions on Advanced Computing and Systems | Volume 2, Issue 1: 53-60, 2026 | DOI: 10.62762/TACS.2025.603512
Abstract
Simulation-driven optimization of complex engineering systems increasingly demands intelligent frameworks capable of replacing exhaustive parameter sweeps with rapid, learned predictions. This paper presents a general surrogate optimization framework that couples high-fidelity simulation with a machine learning regression model to predict system performance and select optimal configurations without exhaustive re-simulation. Fiber-optic dispersion compensation is adopted as a representative benchmark: selecting the optimal placement strategy for dispersion-compensating fiber (DCF)-pre-, post-, or symmetrical-across varying system parameters is computationally expensive, making it an ideal t... More >

Graphical Abstract
Dispersion-Compensating Method for High-Capacity Fiber-Optic Communication System Using Machine Learning Optimization