バイオグラフィー
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.
研究の興味
Machine & Deep Learning, Cryptography, Information Security, Multimedia Encryption and Chaos Theory, AI-Based Non-Invasive Healthcare Framework.

Editor
仕事内容
Lecturer
York St John University
School of Science Technology & Health
United Kingdom
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研究論文
- Sorption-based Spectrophotometric Assay for Lead(II) with Immobilized Azo Ligand
- Efficacy of Different Concentrations of Insect Growth Regulators (IGRs) on Maize Stem Borer Infestation
- Designing a Compact High-precision Positioner with Large Stroke Capability for Nanoindentation Devices
- Use of Augmented Reality as a Radiation-free Alternative in Pain Management Spinal Surgeries
- Analytical Expressions of the Markov Chain of K-Ras4B Protein within the Catalytic Environment and a New Markov-State Model
- The Influence of Dynamical Downscaling and Boundary Layer Selection on Egypt’s Potential Evapotranspiration using a Calibrated Version of the Hargreaves-samani Equation: RegCM4 Approach
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