Dr Oras Al Hassani PhD, MSc, BSc, PGDip.

Currently reading: Research and Key Exchange projects

Biography

Dr. Oras Al Hassani is Associate Professor and Course Leader for MSc Cyber Security and MSc Cyber Security Management.

With over 25 years of expertise in academia, research, and industry collaboration, he has contributed to the advancement of AI and Cybersecurity through innovative teaching, impactful research and global partnerships. Dr. Al Hassani has authored over 47 peer-reviewed publications, including IEEE works, and two acclaimed books on AI. He serves on editorial boards for international journals and has fostered collaborations with universities worldwide, driving joint research and funded initiatives. 

Ravensbourne University, London
Associate Professor and Course Leader for MSc Cyber Security and MSc Cyber Security Management

Research and Key Exchange projects

  • Predictive Modelling for Pandemic Forecasting: A COVID-19 Study in New Zealand and Partner Countries

Publications

Credited as Oras Baker.

  • Book in Springer Nature: Subaramaniam, K., Herawan, T., Baker, O. F., & Palaniappan, S. (2025). Strategic information systems in the digital age: Innovations, technologies, and human-centric perspectives. Springer Nature. (Springer's Book Series - Information Systems Engineering & Management (ISEM)
     
  • Baker, O., Subramaniam, K., Palaniappan, S., & Nowroozi, E. (2025). Detecting and mitigating adversarial examples in neural networks: An enhanced PGD approach. In Adversarial example detection and mitigation using machine learning. Springer.
     
  • Baker, O., Ziran, Z., Mecella, M., Subaramaniam, K., & Palaniappan, S. (2025). Predictive Modeling for Pandemic Forecasting: A COVID-19 Study in New Zealand and Partner Countries. International Journal of Environmental Research and Public Health, 22(4), 562. 
     
  • O. Baker, W. Li, H. Ma, K. Subaramaniam, D. Lopez and S. Palaniappan, 
    Machine Learning-Driven Container Scheduling for Edge-Empowered Microservices, 2025 IEEE International Conference on Robotics and Technologies for Industrial Automation (ROBOTHIA), Kuala Lumpur, Malaysia, 2025, pp. 1-6, doi: 10.1109/ROBOTHIA63806.2025.10986316.
     
  • O. Baker, D. Lopez, W. Li, H. Ma, K. Subaramaniam, and S. Palaniappan, "A Deep Learning-Based Approach Using MTCNN and FaceNet for Automated Attendance and Security Monitoring Systems," in Proc. 7th IEEE Symposium on Computers & Informatics (ISCI 2025), Kuala Lumpur, Malaysia, Aug. 9, 2025, Accepted.
     
  • O. Baker, Z. Ziran, M. Mecella, K. Subaramaniam, S. Palaniappan, and Q. Nguyen, "Improving melanoma diagnosis in New Zealand: A deep learning framework with ResNet50 and generalisability analysis," International Journal of Environmental Research and Public Health (IJERPH), submitted, Feb. 10, 2025.
     
  • L. K. Xiong, K. Subaramaniam, U. E. M. Shah, A. S. B. Shibghatullah, and O. Baker, "Low-light image enhancement with color space (Cielab)," in 2025 International Conference on Artificial Life and Robotics (ICAROB2025), J:COM Horuto Hall, Oita, Japan, Feb. 13–16, 2025.
     
  • W. Z. Bang, K. H. Keoy, K. Subaramaniam, S. Palaniappan, and O. Baker, Crimes identification system for campus safety and the threat of suspicious student conduct, in 2025 International Conference on Artificial Life and Robotics (ICAROB2025), J:COM Horuto Hall, Oita, Japan, Feb. 13–16, 2025.
     
  • O. Baker, W. Li, and D. Liu, Advanced web optimization: Leveraging neural collaborative filtering and prefetching for enhanced user responsiveness, in 2024 IEEE 7th International Conference on Electrical, Electronics and System Engineering (ICEESE), Kanazawa, Japan, 2024, pp. 1–6, doi: 10.1109/ICEESE62315.2024.10828552
     
  • O. Baker, W. Li, and Q. Yuan, "Advanced human motion detection and precision movement measurement via mobile devices using YOLOv8, R-CNN, and augmented reality," in 2024 International Symposium on Networks, Computers and Communications (ISNCC), Washington, DC, USA, 2024, pp. 1–6, doi: 10.1109/ISNCC62547.2024.10758935.
     
  • O. Baker, A. Rehman, O. Basas, and J. Liu, Deep learning for intelligent customer service automation: Development of GRU, LSTM, and recurrent neural network architectures for chatbot applications, in 2024 International Conference on Information Technology Research and Innovation (ICITRI), Jakarta, Indonesia, 2024, pp. 111–117, doi: 10.1109/ICITRI62858.2024.10699245.