Dr Muhammad Hammad Saleem
School of Science, Engineering & Environment
Current positions
Lecturer in Artificial Intelligence
Biography
Dr Muhammad Hammad Saleem is a computer scientist with more than 9 years of combined working experience in academia and industry. He has served prestigious engineering universities/institutes and the electricity industry. He worked at NED University of Engineering & Technology, Pakistan as a Lecturer from 2016-2019, at Manukau Institute of Technology, New Zealand as a Research Assistant in 2022, and at Horizon Networks, New Zealand as an Asset Information Analyst from 2022-2023.
He received his B.E. and M.Engg. degrees from NED University of Engineering and Technology, Pakistan in 2016 and 2018, respectively. He received his Ph.D. degree in 2023 from Massey University, New Zealand. His Ph.D. research consists of developing novel deep learning-based approaches for agricultural problems. His Ph.D. thesis was included in the Dean's List of Exceptional Doctoral Theses.
He has supervised several postgraduate and undergraduate students in their projects and theses/dissertations. He has taught various undergraduate and postgraduate modules during his career. He has co-authored 15 research papers (2000+ Google Citations, 12 h-index, 12 i10-index), including in leading international journals and peer-reviewed international conference proceedings. His research interests include applied AI, image processing, deep learning, computer vision, precision agriculture, and agricultural automation. He is an invited reviewer for numerous world-leading high-impact journals from IEEE, Springer, Wiley, and MDPI.
He has been working as a Lecturer in Computer Science - Artificial Intelligence / Machine Learning in the School of Science, Engineering, and Environment at the University of Salford, United Kingdom since November 2023. He is responsible for teaching undergraduate and postgraduate modules related to data science and AI, supervising the PhD research, MSc projects/dissertation and BSc final year projects, and doing research to address real-life problems by AI-based methods. Currently, he is supervising four full-time PhD students as a joint supervisor who are conducting research on addressing real-world problems in the agriculture and oil and gas industries using machine learning. Recently, he received a successful outcome for an Innovate UK funding call on "Knowledge Transfer Partnership" to develop an AI-based digital asset management platform for a construction company worth around £269k.
Areas of Research
Deep Learning
Machine Learning
Computer Vision
Data Analytics
Precision Agriculture
Areas of Supervision
Machine Learning and Deep Learning to address real-world problems in agriculture, medical, electricity, and construction industries.
Advanced Databases
Computer Programming
Machine Learning and Data Mining
Natural Language Processing
Qualifications
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Doctor of Philosophy
2019 - 2023 -
Master of Engineering
2016 - 2018 -
Bachelor of Engineering
2012 - 2016
Recognitions
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Dean's List of Exceptional Doctoral Theses
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2021 Plants Best paper award
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Kia Kotahi Award