Dr. Waqar Shahid Qureshi is a Lecturer in the School of Computer Science at the University of Galway, with over 21 years of professional experience spanning academia, research, and industry. His expertise lies in artificial intelligence, computer vision, robotics, and intelligent systems, with a strong emphasis on real-world applications in precision agriculture and civil infrastructure. Throughout his career, he has led and contributed to numerous multidisciplinary projects involving AI-driven image analysis, autonomous drones, and sensor-based automation. At the University of Galway, he teaches digital image processing, applied AI, and programming fundamentals, while previously at the National University of Sciences and Technology (NUST) in Pakistan, he taught machine vision, robotics, DSP, and object-oriented programming at both undergraduate and graduate levels. He has supervised numerous master's theses, co-supervised PhD research, and mentored several undergraduate capstone teams. Dr. Qureshi has served as principal investigator and co-investigator on a wide range of research projects, including automated pavement assessment using deep learning, smart spraying systems for agricultural drones, multispectral imaging for precision farming, and mobile-based fruit maturity estimation tools. He is also the co-founder of Robotiqs Private Limited, a pioneering AgriTech startup that introduced commercial aerial spraying drones in Pakistan. In addition to his technical contributions, he has played an active role in policy development related to drones and 3D printing and continues to collaborate with research and industry partners across Europe, Asia, and the Middle East. His work reflects a strong commitment to academic entrepreneurship and the translation of research into innovative, impactful solutions.

My research interest lies in the application of artificial intelligence (AI) to create effective solutions and technologies utilizing affordable sensing systemsfor real-world environmental monitoring, and various visual analyses in the areas of precision agriculture, horticulture, and civil engineering.My expertise encompasses 3D computer vision, automated image analysis, and automated analysis of NIR spectral analysis using point spectroscopy or satellite imagery. Additionally, my proficiency extends to robot localization and target tracking. A specific focus of my interest lies in aerial robotics, with a particular emphasis on low-altitude flying. I am intrigued by challenges related to localization and mapping in this context, aiming to advance the field and address real-world applications. From 2016 - 2023, I won various research grants and development projects. The following list provides details of my research grants: Research Grant by Enterprise Ireland · Automated road pavement condition assessment - a deep learning approach - Enterprise Ireland Marie Curie Career Fit FellowshipInternational Software and Hardware Development Projects · Development of FreMEn advisory notification App - CTU Prague (Project Funds: 3000 USD, 0320 - 0520)· Development of Farmer App for crop health and crop input (Project Funds: 3000 USD, 0520 - 0820)· Development of Cough Audio recording App and Contact Tracing App for Umm-ul-Qura University (Project Funds: 6,000 USD, 0720-0920) Higher Education Commission of Pakistan· National Research Program University - 2021 (Grant: 50,000 USD, 621-624), Design and development of smart spraying system for agricultural drones. · Technology Development Program - 2018 (Grant: 76,500 USD, 718-620), Low-cost precision agriculture services using high-resolution multi-spectral imaging and map­ping software.· Public - No restriction Sector Development Project - 2018 (Grant: 615,384 USD, 718-1220), Establishment of Robot and Design and Development Lab Agriculture Domain (specified projects), NCRA· HEC startup research grant - 2016 (Grant: 4500 USD, 816-1217), Indigenous Development of Robotic Arm Using Rapid Prototyping Techniques for Application Such as in Field Crop Monitoring. · HEC startup research grant - 2017 (Grant: 4500 USD, 217-218), Development of a low-cost teleoperated sprayer drone for precision agriculture.Pakistan Agriculture Research Council · Agriculture Linkage Program - 2018 (Grant: 40,600 USD, 718-1220), Smart Phone Based on-tree Mango Fruit Quantity and Quality Estimation using near In­frared Spectroscopy and Machine Vision.h2h2h2h2

Computer Vision, Digital Image Processing, Applied Artificial Intelligence, Machine Learning, Computer Organisation and Design, Digital Design, Electronics, Data Structures, Object Oriented Programming, Programming Languages, Programming for Embedded Systems, Real Time Embedded Systems