Mr Imad Gohar | Defect Detection | Best Researcher Award

PhD Candidate, Heriot-Watt University, Malaysia

Imad Gohar is a PhD candidate in Computer Engineering at Heriot-Watt University Malaysia, specializing in autonomous aerial-based visual monitoring of wind turbine blade surface defects. His expertise spans renewable energy, computer vision, object detection, deep learning, and machine learning. With extensive teaching and research experience, he has contributed to several impactful publications and projects. Imad has earned recognition for his academic achievements, including a gold medal for securing the top position in his undergraduate studies.

PROFESSIONAL PROFILE

Google Scholar

STRENGTHS FOR THE AWARDS

1. Academic Excellence: Imad Gohar has consistently demonstrated academic brilliance, as evidenced by his Gold Medal for achieving the top rank in his undergraduate Computer Science program.
2. Cutting-Edge Research: His PhD work on autonomous aerial-based visual monitoring of wind turbine blade defects addresses a critical challenge in renewable energy, making a significant contribution to sustainable development and machine learning applications.
3. Diverse Teaching Experience: Gohar’s extensive teaching experience at prestigious institutions like Heriot-Watt University and NUST showcases his ability to impart knowledge and mentor future professionals effectively.
4. Publications with Impact: His research output, including papers on person re-identification, defect detection, and advanced CNN-RNN architectures, reflects both technical depth and practical application, with citations highlighting peer recognition.
5. Interdisciplinary Expertise: By combining renewable energy, computer vision, and deep learning, Gohar demonstrates a strong interdisciplinary approach, a hallmark of leading researchers.

AREAS FOR IMPROVEMENTS

1. Collaboration and Visibility: While Gohar has strong publications, increasing international collaboration and participation in global research initiatives could further enhance his visibility and network in the research community.
2. Broader Research Applications: Expanding his work beyond defect detection to include predictive maintenance or real-time monitoring could attract more practical implementations and industry partnerships.
3. Funding and Grants: Actively securing research grants and leading large-scale projects could establish him as a principal investigator with leadership in innovative research.

EDUCATION

Imad Gohar is pursuing his PhD in Computer Engineering at Heriot-Watt University Malaysia (2022–2025), focusing on aerial-based defect detection in wind turbines. He completed his Master’s in Computer Science from NUST, Pakistan (2019), with a thesis on person re-identification using unsupervised learning techniques. His Bachelor’s in Computer Science from ICS&IT Peshawar, Pakistan (2016), emphasized algorithms, and his thesis introduced a web-based educational counseling expert system. Imad’s academic journey reflects his dedication to advancing innovative solutions in computing and engineering.

EXPERIENCE

Imad is a Teaching Assistant at Heriot-Watt University Malaysia (2022–present), conducting tutorials in programming and software engineering. He previously served as an Associate Lecturer at Capital University of Science and Technology, Islamabad (2021), teaching core computer science courses and supervising projects. As a Lab Engineer at NUST (2019–2020), he managed lab demonstrations and documentation. Imad also held lecturer roles at AUST and GCT, teaching diverse computing courses. His professional career highlights a blend of academic and technical expertise.

AWARDS AND HONORS

Imad was awarded the Undergraduate Performance Award (Gold Medal) by ICS&IT Peshawar in 2016 for achieving the top rank in Computer Science. This recognition underscores his academic excellence and commitment to innovation. Throughout his career, Imad has consistently demonstrated exceptional dedication to his field, earning accolades for his research and teaching contributions. His achievements reflect a deep passion for advancing technology and inspiring others in the academic and professional community.

RESEARCH FOCUS

Imad’s research focuses on renewable energy, computer vision, and deep learning. His work in autonomous visual monitoring and defect detection for wind turbine blades aims to improve operational efficiency in renewable energy systems. He explores innovative approaches, including rotated bounding boxes and aerial imagery, to address challenges in defect detection. His interests also encompass machine learning applications in person re-identification and advanced object detection techniques.

PUBLICATION TOP NOTES

• 📖 Person re-identification using deep modeling of temporally correlated inertial motion patterns
• 📖 Two stream deep CNN-RNN attentive pooling architecture for video-based person re-identification
• 📖 Slice-Aided Defect Detection in Ultra High-Resolution Wind Turbine Blade Images
• 📖 Automatic Defect Detection in Wind Turbine Blade Images: Model Benchmarks and Re-Annotations
• 📖 Optimizing Wind Turbine Surface Defect Detection: A Rotated Bounding Box Approach
• 📖 Review of state-of-the-art surface defect detection on wind turbine blades through aerial imagery: Challenges and recommendations

CONCLUSION

Imad Gohar’s exceptional academic achievements, impactful publications, and contributions to both teaching and applied research make him a strong contender for the Best Researcher Award. By continuing to expand his collaborative efforts and exploring broader applications of his work, he could further solidify his position as a leader in renewable energy and computer vision research.