Muhammad Shahbaz Ayyaz

Lecturer
  • Department of Computer Science
  • Shahbaz.Ayyaz@nu.edu.pk
  • (041) 111-128-128
  • Ext: 176

Introduction

Mr. M. Shahbaz Ayyaz joined FAST National University of Computer and Emerging Sciences (FAST-NUCES) in 2022 as an Instructor of Computer Science and was promoted to Lecturer in Computer Science in 2023. He holds an MS in Computer Science from the University of Gujrat and a Bachelor’s degree from the University of Sargodha.

He is currently a PhD scholar conducting research on Hyperspectral Image Classification, with a focus on deep learning and advanced computational techniques. He is also a recipient of the Higher Education Commission (HEC) International Research Support Initiative Programme (IRSIP) Scholarship, Batch 59.

He began his professional career as an Instructor at Resource Academia International System and later served as a Lecturer at Superior College, Gujrat Campus. Before joining FAST-NUCES, he worked as a Lecturer at the University of Gujrat.

His research interests include hyperspectral imaging, computer vision, medical imaging, and machine learning. His research has been published in international peer-reviewed journals, including IEEE Geoscience and Remote Sensing Letters and Diagnostics.

Research Interests

  • Hyperspectral Imaging and Classification
  • Computer Vision
  • Medical Imaging
  • Machine Learning and Deep Learning

 

Scholarships and Awards

HEC International Research Support Initiative Programme (IRSIP) Scholarship, Batch 59.

Education

  • PhD in Computer Science (In Progress)
  • MS in Computer Science, University of Gujrat, (2020)
  • BS in Software Engineering, University of Sargodha, (2017)

Publications

  1. M. S. Ayyaz et al., “Spiking Morphological Mamba for Hyperspectral Image Classification,” IEEE Geoscience and Remote Sensing Letters, vol. 23, Art. no. 5506605, 2026. DOI: https://doi.org/10.1109/LGRS.2026.3719487
    Impact Factor: 4.8
  2. M. S. Ayyaz et al., “Hybrid Deep Learning Model for Endoscopic Lesion Detection and Classification Using Endoscopy Videos,” Diagnostics, 2022. DOI: https://doi.org/10.3390/diagnostics12010043

Collaborations at National and International Level

Detail of Funded Projects