Muhammad Jawad Bashir is a PhD candidate at Atlantic Technological University (ATU) under the TU Rise MATX programme, supervised by Dr. Shagufta Henna with Dr. Eoghan Furey as co-supervisor. His research focuses on sustainable precision farming, specifically the development of explainable AI and self-supervised generative learning frameworks that leverage the Internet of Robotic Things (IoRTs) within a Digital Twin environment.
His work aims to integrate IoRT-driven sensor data with a real-time digital representation of greenhouse systems to support monitoring, crop planning, forecasting, and resource optimisation in controlled agricultural settings. Through the use of explainable AI (XAI), the research seeks to enhance transparency and interpretability of model outputs, enabling farmers and stakeholders to better understand data-driven insights and AI-supported decisions. The broader objective is to advance climate-resilient, sustainable farming practices that improve productivity while reducing environmental impact, and to support the trustworthy deployment of AI-enabled robotic and automated systems in agriculture.
Previously, he completed his Master’s degree at the National University of Sciences and Technology (NUST), Pakistan, where his thesis focused on crop growth and disease monitoring using UAV-based imaging and computer vision. He also worked as a Research Assistant on the “Multifaceted Crop Scouting using Industry 4.0” project, contributing to the deployment and experimental evaluation of an automated farming robot (FarmBot). Overall, his work aims to bridge advanced AI methods with practical agricultural needs, supporting the development of reliable, transparent, and sustainable smart farming systems.
