Dr Imad Gohar

Imad Gohar

Dr Imad Gohar

  • Lecturer
Department of Smart Computing and Cyber Resilience
  • School of Computing and Artificial Intelligence
Faculty of Engineering and Technology
SDGs Focus

Biography

Dr. Imad Gohar is advancing the frontier of AI-driven computer vision and intelligent automation. He earned his PhD from Heriot-Watt University under the prestigious James Watt Scholarship, where his research focused on developing AI-powered visual inspection systems for wind turbine blades using drone imagery.

A recipient of multiple academic honour's, Dr. Imad earned a Gold Medal in his bachelor’s degree in computer science, won the Best Presentation Award at the Heriot-Watt University PGR Conference, and received a Best Paper Award at an IEEE International Conference.

He has served in academic and research roles at HWU, NUST, ITU, and CUST university, including leading the Samsung Innovative Campus program and AI Summer School. His work spans smart infrastructure monitoring, remote sensing, and human-centered sensing systems, with publications in top-tier journals and international conferences.

As an Associate Fellow of the Higher Education Academy (AFHEA), Dr. Imad is well-versed in modern pedagogical and quality assurance frameworks, including Outcome-Based Education (OBE), Table 4 preparation, Continuous Quality Improvement (CQI), and rubrics development. He remains committed to advancing AI for sustainability, intelligent systems, and digital transformation.
 

Academic & Professional Qualifications

  • PhD - Program, Engineering and Engineering Trades, Department of Electrical, Electronic and Computer Engineering, School of Engineering and Physical Science (EPS) Heriot-Watt University (2025)
  • MS(CS) - Computer Vision - National University of Science and Technology - Pakistan (2019)
  • BS(CS) - Algorithms - Institute of Computer Sciences and Information Technology (ICS/IT) - Pakistan (2016)

Research Interests

  • Computer Vision
  • Digital Image Processing
  • Industrial automation
  • Emotion Detection
  • Expression Analysis
  • Smart Infrastructure Monitoring
  • Remote sensing
  • Human Activity Recognition
  • Inertial and Visual Sensors Data Processing
  • Person Re-Identification and Group Re-Identification

Teaching Areas

  • Computer Vision
  • Artificial Intelligence & Machine Learning
  • Python Programming for AI and Data Science
  • Core Computer Science courses
  • Digital Image Processing, Data Visualization and Ubiquitous Computing

Courses Taught

  • Computer Vision
  • Micro-credential in Computer Mathematics Fundamentals
  • Database Management Systems

Notable Publications

  1. Person Re-identification Using Deep Modeling of Temporally Correlated Inertial Motion Patterns
    Focus: Wearable sensor data, inertial signals, human movement modeling
    SDG: #9 - Industry, Innovation and Infrastructure
  2. Two-Stream Deep CNN-RNN Attentive Pooling Architecture for Video-Based Person Re-identification
    Focus: Deep learning for identity tracking in surveillance systems
    SDG: #11 - Sustainable Cities and Communities, #9 - Industry, Innovation and Infrastructure
  3. Slice-Aided Defect Detection in Ultra High-Resolution Wind Turbine Blade Images
    Focus: Novel slice-based inference technique for analyzing large turbine blade images
    SDG: #7 - Affordable and Clean Energy, #9 - Industry, Innovation and Infrastructure, #13 - Climate Action
  4. Automatic Defect Detection in Wind Turbine Blade Images: Model Benchmarks and Re-Annotations
    Focus: Benchmarking defect detection models and enhancing dataset quality
    SDG: #7 - Affordable and Clean Energy, #9 - Industry, Innovation and Infrastructure
  5. Review of State-of-the-Art Surface Defect Detection on Wind Turbine Blades Through Aerial Imagery: Challenges and Recommendations
    Focus: Comprehensive literature review; highlights gaps and future directions
    SDG: #7 - Affordable and Clean Energy, #9 - Industry, Innovation and Infrastructure, #13 - Climate Action
  6. Optimizing Wind Turbine Surface Defect Detection: A Rotated Bounding Box Approach
    Focus: Oriented object detection for better localization of defects on curved surfaces
    SDG: #7 - Affordable and Clean Energy, #9 - Industry, Innovation and Infrastructure

Achievements & Accolades

Best Paper Award (ISPACS 2025, Bandung, Indonesia)
Heriot-Watt University, James-Watt Scholarship (Ph.D.)
Best Presentation Award (HWU PGRC 2025)
Gold Medal (BS Degree)

Professional Associations

Associate Fellow of Higher Education Agency (AFHEA)