Dr Hafeez Ur Rehman

Associate Professor
School of Computing and Data Science

Academic Qualifications

2014, Polytecnic University of Turin, Turin, Italy, PhD in Computer and Control Engineering
2010, Polytechnic University of Turin, Turin, Italy, MS in Computer Communication and Networks Engineering
2006, COMSATS University, Islamabad, Pakistan, BS in Computer Science

Professional Experience

With over a decade of experience as an Associate Professor and Head of the Computer Science Department at the National University of Computer & Emerging Sciences in Islamabad, Pakistan, Dr. Hafeez brings a wealth of knowledge and expertise to Oryx Universal College with Liverpool John Moores University. He has actively contributed to both academia and research in the field of computer science. His service in various administrative roles, including heading the School of Computing and chairing the industrial advisory board, reflect his commitment to advancing academic leadership and strengthening ties between academia and industry. He is renowned for his contributions to artificial intelligence, machine learning, and computational biology, and contributing to his mission of excellence in computer science education.

Research Interests

The primary research focus of Dr. Hafeez is in computational biology and medical imaging and is evident through a robust publication record in esteemed journals such as Genome Biology, Journal of Grid Computing, Plos-One and PeerJ Computer Science. He has principally authored 30+ journals and conferences; all published in well-reputed international avenues. He has over 1000+ citations with a 70+ cumulative Impact Factor. His guidance has facilitated the successful supervision of numerous Bachelor's, Master's, and Doctoral candidates, whose scholarly undertakings span the globe

Selected Publications

Omar, M., Ur Rehman, H.*, Samin, O. B., Alazab, M., Politano, G., & Benso, A. (2023). CapGAN: Text-to-Image Synthesis Using Capsule GANs. Information, 14(10), 552
Mansoor, M., Nauman, M., Ur Rehman, H., & Omar, M. (2022). Gene Ontology Capsule GAN: An Improved Architecture for Protein Function Prediction. PeerJ Computer Science, 8, e1014
Mansoor, M., Nauman, M., Ur Rehman, H., & Benso, A. (2022). Gene Ontology GAN (GOGAN): A Novel Architecture for Protein Function Prediction. Soft Computing, pp. 1-15