Inspires a love for learning in everyone.
Fosters collaboration and teamwork.
Helps students see their full potential.
Creates a collaborative and inclusive space.
Fareed Ud Din is a Senior Lecturer in the School of Science and Technology at the University of New England. He is a computer scientist whose research interests include Artificial Intelligence, Distributed Computing, Multi-Agent Systems, Information Systems, and Industry 4.0. Ud Din received his PhD in Computer Science from the University of Newcastle, NSW, on a fully-funded non-Commonwealth Government of Australia scholarship, completing it in an exceptional timeframe. He also holds a BS in Computer Science, an MS in Computer Science, and is a Certified Associate in Project Management (CAPM). With no less than six years of uninterrupted teaching and research experience in Australia and Pakistan, he has been part of interdisciplinary research groups such as the IoT Research Group at Information Technology University, Lahore, and the Distributed Computing Research Group at the University of Newcastle.
Ud Din's research extends to Cyber-Physical Systems, Applied Artificial Intelligence in Health, and Applied Machine Learning in Health, covering areas like explainable AI for mortality prediction, dementia detection and prognosis, depression assessment, mental health decision-making, and medicinal plant identification. During his PhD tenure at the University of Newcastle, he earned several academic performance awards, including Best Research Paper Award (2018), Best Technical Poster Award (2018), Best Academic of the Year Award (2019), and Best Conference Presentation Award (2020). His key publications include "Using Artificial Intelligence (AI) to predict organizational agility" (PLoS ONE, 2023), "Predicting Postgraduate Student Engagement Using Artificial Intelligence (AI)" (IEEE Transactions on Artificial Intelligence, accepted 2024), "Explainable AI for mortality prediction: a comparative study using the MIMIC-III dataset" (2026), "A Systematic Review of Medicinal Plant Identification Using Deep Learning" (2024), "AOSR 2.0: A Novel Approach and Thorough Validation of Agent Oriented Storage and Retrieval WMS planner for SMEs under Industry 4.0" (Future Internet, 2021), "Agent-Oriented Smart Factory (AOSF): An MAS Based Framework for SMEs Under Industry 4.0" (KES-AMSTA, 2018), and "Formalisation of Problem and Domain Definition for Agent Oriented Smart Factory (AOSF)" (IEEE TENSYMP, 2018). He teaches courses in Programming, Computer Science, Software Engineering, Information Systems, and Project Management.
