Prof. Abdulle Hassan Mohamud

Senior Computer Scientist and University Professor with over two decades of experience in the teaching profession, research and academic leadership. Prof. Abdulle Hassan Mohamud holds an MSc in Computer Science from Assumption University and currently a PhDCS scholar at Asia University. His academic and research pursuits span across multitude SME disciplines in Artificial Intelligence, Cryptology, Computational Complexity, and Numerical Optimization. A respected scholar and educator, Prof. Abdulle has contributed significantly to the advancement of Anomaly Detection / Pattern Recognition Systems, Neural Network Algorithms, and Enhanced Cryptographic Techniques. His work bridges theoretical computations with applied Security and Intelligent Systems, reflected in publications presented at prestigious IEEE and International Conferences. As a dedicated Faculty Member, Prof. Abdulle teaches AI, Numerical Methods, Image Processing, Algorithm Analysis and Design, while actively mentoring research and development in emerging Computer Science domains. Prof. Abdulle is recognized for excellence in teaching, innovation and research, having received numerous awards of best paper and teaching. A member of IEEE and ACM, he is committed to guiding future technologists through impactful education and the development of robust, intelligent digital systems.

Artificial Intelligence, Cryptology, and Algorithm Design and Optimizations

• Pattern Recognition & Machine Learning
• Cryptology
• Algorithmic Complexity & Computability
• Numerical Analysis & Optimization Methods
• Secure System Design

• Artificial Intelligence
• Digital Image Processing
• Research Methods
• Analysis & Design of Information Systems
• Analysis & Design of Algorithms
• Computer Architecture

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1. Abdulle, H. (2025). A new mathematical model to improve encryption process based on Split-Radix Fast Fourier Transform algorithm. Frontiers in Computer Science. https://doi.org/10.3389/fcomp.2024.1479592
2. Abdulle, H. (2023). Breadth First Search Job Scheduler Based on Backpropagation Neural Network with Levenberg Marquardt Algorithm. 3rd Int’l Conference on Electrical, Computer and Energy Technologies (ICECET 2023), 1–12. https://ieeexplore.ieee.org/document/10389240
3. Abdulle, H. (2018). Fruit Feature Recognition Based on Unsupervised Competitive Learning and Backpropagation Algorithms. 4th Int’l Conference on Engineering, Applied Sciences, and Technology (ICEAST 2018), 21–33 https://ieeexplore.ieee.org/document/8434481