简历
I am Mujeeb Ur Rehman, and I hold a position as a Lecturer at York St John University, Department of Data Science. My research focus during my Ph.D. was on Artificial Intelligence and Cybersecurity.
Prior to my current position, I served as a researcher in the James Watt School of Engineering at the University of Glasgow, UK. With over 10 years of experience, I am an experienced educator with cutting-edge teaching and research expertise in AI, Machine Learning, Cybersecurity, and IoT, having worked in academic, research, and industry environments. I have taught numerous industry-relevant courses, including Artificial Intelligence, Machine Learning, Neural Networks, AI for Cybersecurity, Programming for Cybersecurity, Cryptography, Computer Systems, and Mathematics for Computing.
As a supervisor, I have overseen several dissertations from PhD, MSc, and undergraduate students. My contribution to the research community includes co-authoring more than 28 research papers, published in leading international journals and peer-reviewed international conference proceedings. In recognition of my contributions to the field of Artificial Intelligence and Cybersecurity, I was awarded the Global Talent status by the UK Research and Innovation Body and the Royal Academy of Engineering in 2022.
研究兴趣
Machine & Deep Learning, Cryptography, Information Security, Multimedia Encryption and Chaos Theory, AI-Based Non-Invasive Healthcare Framework.

Editor
工作详情
Lecturer
York St John University
School of Science Technology & Health
United Kingdom
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研究文章
- Preparing for SpaceX Mission to Mars
- Abrasive Wear in Some High Fe-Cr-C Alloy in Cement Powder
- Physical Activity and Lifestyle of Female Students of the Faculty of Health Sciences University of Applied Sciences in Tarnów (Poland)
- Examining the Causal Connection between Lipid-lowering Medications and Malignant Meningiomas through Drug-target Mendelian Randomization Analysis
- Federated Learning- Hope and Scope
- Sensor-based Sorting using De-XRT Sensor Applied to a Greenfield Copper Ore Project in Southern Brazil
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