Dr Syed Muhammad Zubair Rehman Gillani

Assistant Professor
sgillani@su.edu.om
Phone: +968 26850100 Extn: 221
Location: Rustaq Building

Biography

Dr. Syed Muhammad Zubair Rehman Gillani is an esteemed Assistant Professor at the Faculty of Computing & IT (FCIT) in Sohar University, located in the Sultanate of Oman. With an impressive academic background and years of experience, he has made significant contributions to the field of Information.

Dr. Rehman embarked on his postdoctoral research journey from 2019 until September 2021, gaining invaluable experience at prestigious institutions. He first pursued his postdoctoral research at the Universiti Malaysia Pahang (www.ump.edu.my) in 2019, followed by a stint at Universiti Tun Hussein Onn Malaysia (UTHM, www.uthm.edu.my) in 2021. These research experiences allowed him to further refine his expertise and broaden his perspectives in the field.

Dr. Rehman completed his Doctor of Philosophy (PhD) in Information Technology from UTHM in 2016. He then commenced his career as an Assistant Professor in the Department of Computer Science and IT at the University of Lahore. His dedication to teaching and research became evident as he accumulated more than 10 years of experience in the educational industry.

Dr. Rehman’s educational journey began with a Master of Science (MS) degree in IT from UTHM in 2012. Prior to that, he completed his Bachelor of Science (BS) in Computer Science from PUCIT, University of the Punjab (www.pu.edu.pk) in Pakistan in 2008. These academic achievements provided him with a solid foundation and equipped him with the necessary knowledge and skills to excel in his field.

Throughout his career, Dr. Rehman has showcased his intellectual prowess through the publication of over 50 research articles. These articles have been featured in reputable journals and conferences indexed in both ISI (Institute for Scientific Information) and Scopus databases. His research interests primarily lie in the field of search-based software engineering, optimization, hybrid neural networks, as well as noise and vibration hazards. This diverse range of interests demonstrates his versatility and commitment to exploring various aspects of Information Technology.

Dr. Rehman’s contributions to academia extend beyond his publications. He actively participates in conferences and workshops, both as a presenter and as a member of scientific committees. By engaging with peers and experts in the field, he contributes to the exchange of knowledge and the advancement of research.

In addition to his academic pursuits, Dr. Rehman is dedicated to promoting the practical applications of his research findings. He strives to bridge the gap between academia and industry, ensuring that his work has real-world implications and benefits. By fostering collaborations and partnerships with organizations, he aims to drive innovation and make a positive impact on society.

Dr. Rehman’s accomplishments as an Assistant Professor and researcher have earned him recognition and respect within the academic community. His continuous pursuit of knowledge and his commitment to pushing the boundaries of Information Technology highlight his passion for his chosen field. As he continues to evolve and contribute to the field, it is certain that Dr. Rehman will make further notable contributions to research and education in the years to come.

Qualification

• Ph.D. in Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia, 2016.
• MS in Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia, 2012.
• BS (HONS) in Computer Science, University of the Punjab, Pakistan, 2008.

Teaching Interest

• Algorithm Design
• Geographical Information Systems
• Spatial Databases
• Mobile Application Development
• Object-Oriented Programming
• Data Mining
• Artificial Intelligence
• Data Structures
• Systems Design and Modeling
• Game Development

Research Interest

• Swarm Intelligence
• Optimization​
• Social Collaborative Networks

Publications

• ​​Rehman, M.Z., Zamli, K. Z., Almutairi, M., Chiroma, H., Aamir, M., and Kader, M. A. (2021). A novel state space reduction algorithm for team formation in social networks. PLoS ONE. 16(12).​
• ​​Shahzad, A., Nawi, N. M., Rehman, M. Z., and Khan, A. (2021). An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach. COMPLEXITY. 2021.
• Rehman, M. Z., Khan, A., Ghazali, R., Aamir, M., Nawi, N. M. (2021). A new Multi Sine-Cosine algorithm for unconstrained optimization problems. PLoS ONE. 16(8).
• Rehman, M. Z., Mohd. Nawi, N., Arshad, M., & Khan, A. (2021). Recognition of Cursive Pashto Optical Digits and Characters with Trio Deep Learning Neural Network Models. Electronics, 10(20), 2508.
• Aamir, M., Nawi, N.M., Wahid, F., Hasan Zada, M. S., and Rehman, M. Z. (2021). Hybrid Contractive Auto-encoder with Restricted Boltzmann Machine For Multiclass Classification. Arab Journal of Science and Engineering 46.
• Rehman, M.Z., Zamli, K. Z., and Nasser, A. 2020. An Improved Genetic Bat algorithm for Unconstrained Global Optimization Problems. 9th International Conference on Software and Computer Applications (ICSCA 2020). Malaysia.
• Rehman, M. Z., Tanveer, A., Nawi, N. M., Zamli, K. Z. (2020). Optimized Weight Selection in Levenberg-Marquardt Back-Propagation Using Wolf Search. Lecture Notes in Electrical Engineering, vol 678. Springer, Singapore.
• ​Rehman, M. Z., Nawi, N. M., Tanveer, A., Zafar, H., Munir, H., Hassan, S. (2020). Lungs Cancer Nodules Detection from CT Scan Images with Convolutional Neural Networks. Recent Advances on Soft Computing and Data Mining (SCDM 2020). Advances in Intelligent Systems and Computing, vol 978. Springer.
• Nawi, N. M., Rehman, M. Z., Hamid, N. A., Khan, A., Naseem, R., Uddin, J. (2017). Optimizing Weights in Elman Recurrent Neural Networks with Wolf Search Algorithm. Recent Advances on Soft Computing and Data Mining (SCDM 2016). Advances in Intelligent Systems and Computing, vol 549. Springer.
• Nawi, N. M., Rehman, M. Z., Khan, A., Kiyani, A., Chiroma, H., & Herawan, T. (2016). Hybrid Bat and Levenberg-Marquardt Algorithms for Artificial Neural Networks Learning. Journal of Information Science and Engineering. 32(5)., 1301-1324.