Professional Summary

Consultant, researcher, and technology leader with 22+ years of experience in robotics, aerial drones, computer vision, artificial intelligence, automation, intelligent sensing, and embedded systems. Experience spans academia, industrial R&D, product development, commercialization, and innovation-led consulting.

Core Expertise

• Robotics & Autonomous Systems
• Aerial Drones & UAV Platforms
• Computer Vision & Image Processing
• Artificial Intelligence & Machine Learning
• Automation & Road Assets Analytics
• Embedded Systems & Edge AI
• Multimodal Sensing
• Applied Research & Innovation Leadership
• Academic Supervision & Mentoring
• Programming: Python, C++, Java

Professional Experience

Education

• Doctor of Engineering (D.Eng.)
  Asian Institute of Technology, Thailand
• M.Sc. Engineering
  University of Engineering and Technology, Taxila, Pakistan
• B.Sc. Engineering
  University of Engineering and Technology, Lahore, Pakistan
• Certificate in Teaching & Learning in Higher Education
  University of Galway, Ireland

Patents and Innovation

• Lead inventor of the 3D scanning software embedded in the world's first full-colour 3D printer and scanner commercialized by XYZPrinting Inc.
• Comprehensive and Efficient Pavement Condition Rating using Deep Learning-based Direct Classification Methodology
• The three-dimensional point cloud model generating device and generation method of entity article

Selected Publications

1. Ma, Y., Zhang, W., & Qureshi, W. S. (2021). Autonomous navigation for a Wolfberry picking robot using visual cues and fuzzy control. Information Processing in Agriculture.
2. Qureshi, W. S., Payne, A., Walsh, K. B., Linker, R., Cohen, O., & Dailey, M. N. (2016). Machine vision for counting fruit on mango tree canopies. Precision Agriculture, 17(3), 1–21.
3. Moazzam, S. I., Khan, U. S., Qureshi, W. S., Nawaz, T., & Kunwar, F. (2023). Towards automated weed detection through two-stage semantic segmentation of tobacco and weed pixels in aerial imagery. Smart Agricultural Technology, 4.
4. Tahir, M. N., Lan, Y. B., Zhang, Y. L., Wang, Y. K., Nawaz, F., Shah, M. A. A., Gulzar, A., & Qureshi, W. S. (2020). Real time estimation of leaf area index and groundnut yield using multispectral UAV. International Journal of Precision Agricultural Aviation, 3(1), 1–6.
5. Ghazal, S., Qureshi, W. S., Khan, U. S., Iqbal, J., & Rashid, N. (2021). Analysis of visual features and classifiers for fruit classification problem. Computers and Electronics in Agriculture.
6. Qureshi, W. S., Power, D., Ullah, I., Mulry, B., Feighan, K., McKeever, S., & O’Sullivan, D. (2023). Deep learning framework for intelligent pavement condition rating: A direct classification approach for regional and local roads. Automation in Construction, 153, 104945.
7. Qureshi, W. S., Hassan, S. I., McKeever, S., Power, D., Mulry, B., Feighan, K., & O’Sullivan, D. (2022). An exploration of recent intelligent image analysis techniques for visual pavement surface condition assessment. Sensors.
8. Qureshi, W. S., Ekpanyapong, M., Dailey, M. N., Rinsurongkawong, S., & others. (2015). QuickBlaze: Early fire detection using a combined video processing approach. Fire Technology.
9. Moazzam, S. I., Khan, U. S., Tiwana, M. I., Iqbal, J., Qureshi, W. S., & Shah, S. I. (2019). A review of application of deep learning for weeds and crops classification in agriculture. Proceedings of ICRAI 2019.
10. Moazzam, S. I., Nawaz, T., Qureshi, W. S., Khan, U. S., & Tiwana, M. I. (2023). A W-shaped convolutional network for robust crop and weed classification in agriculture. Precision Agriculture.
11. Rauf, U., Qureshi, W. S., Jabbar, H., Zeb, A., Mirza, A., Alanazi, E., Khan, U. S., & Rashid, N. (2022). A new method for pixel classification for rice variety identification using spectral and time series data from Sentinel-2 satellite imagery. Computers and Electronics in Agriculture, 193.
12. Shahid, R., Qureshi, W. S., Khan, U. S., Munir, A., Zeb, A., & Moazzam, S. I. (2024). Aerial imagery-based tobacco plant counting framework for efficient crop emergence estimation. Computers and Electronics in Agriculture, 217, 108557.
13. Muqaddas, S., Qureshi, W. S., Jabbar, H., Munir, A., & Haider, A. (2024). A comprehensive deep learning approach for harvest ready sugarcane pixel classification using Sentinel-2 multispectral imagery. Remote Sensing Applications: Society and Environment, 35, 101225.
14. Ghazal, S., Munir, A., & Qureshi, W. S. (2024). Computer vision in smart agriculture and precision farming: Techniques and applications. Artificial Intelligence in Agriculture, 13, 64–83.
15. Abbas, S. A., Qureshi, W. S., & Munir, A. (2024). Design and development of an unmanned orchard spraying robot with two degrees of freedom. IECON 2024 – 50th Annual Conference of the IEEE Industrial Electronics Society.
16. Garcia, J. A. A., Shah, S., Baig, M. H., Qureshi, W. S., & Ullah, I. (2025). Enhancing pavement condition assessment: A comprehensive review of affordable sensing technologies for cycle tracks. Proceedings of VEHITS 2025, pp. 676–682.
17. Haider Shah, S. M., Qureshi, W. S., O’Dea, G., & Ullah, I. (2025). Intelligent pavement condition rating system for cycle routes and greenways. Proceedings of VEHITS 2025, pp. 668–675.
18. Baig, M. H., Garcia, J. A. A., Qureshi, W. S., & Ullah, I. (2025). Towards assessing cycleway pavement surface roughness using an action camera with IMU and GPS. Proceedings of VEHITS 2025, pp. 247–255.
19. Akbar, H., Nawaz, T., Asaduzzaman, M., Hasan, M. S., Qureshi, W. S., & Shafait, F. (2025). Lightweight distilled transformer-based vision framework for detection of forest fire and smoke in real-world scenes. Journal of Electronic Imaging, 34(3), 033035.
20. Asif, M., Ur Rehman, F., Rashid, Z., Hussain, A., Mirza, A., & Qureshi, W. S. (2025). An insight on the timely diagnosis of diabetic retinopathy using traditional and AI-driven approaches. IEEE Access, 13, 116869–116886.
21. Asif, M., Tiwana, M. I., Qureshi, W. S., Hussain, S. T., Khan, U. S., & others. (2025). Bio-inspired auto-adaptive framework for optimized movement of passive knee prosthesis. Journal of the Mechanical Behavior of Biomedical Materials.
22. Ahmad, S., Zeb, A., Akbar, H., Ayouni, S., & Qureshi, W. S. (2025). Future-frame prediction for coastal land cover using remote sensing data and deep learning. International Journal of Remote Sensing, 46(17), 6548–6569.
23. Rice, M., Krause, L., & Qureshi, W. S. (2025). EgoDrive: Egocentric multimodal driver behavior recognition using Project Aria. Proceedings of the 1st International Workshop on Gaze Data and NLP, pp. 18–25.
24. Basit, A., Qureshi, W. S., Dailey, M. N., & Krajník, T. (2014). Joint localization of pursuit quadcopters and target using monocular cues. Journal of Intelligent and Robotic Systems.