Rate My Professor Fermi Pasha

Dr. Muhammad Fermi Pasha is a Senior Lecturer in the School of Information Technology at Monash University Malaysia. He earned his PhD in Brain Inspired Computing from Universiti Sains Malaysia in 2010, an MSc in Computer Science in 2006, and a BCompSc (Hons) in Software Engineering in 2003 from the same institution. During his doctoral studies, he worked for four years as a Senior Software Engineer and Architect in the software industry. After completing his PhD, Pasha served as a research fellow at Universiti Sains Malaysia for five years, where he contributed to several multidisciplinary research projects involving community engagement activities. He is currently attached to the Malaysia School of Information Technology, teaching courses such as Introduction to Computer Science, Introduction to Business Information Systems, User Interface Design and Usability, and serving as Chief Examiner for Usability.

Pasha's research specializations include evolving systems and machine intelligence, neocortex memory modelling, intelligent next-generation network monitoring and security, medical image analysis and communication platforms, healthcare data analytics and radiology IT, neuroimaging, computational neuroimaging, intelligent network security traffic analysis, and digital health emphasizing big data. He has received various awards recognizing his software solutions and research projects, both as a team member and lead, including a paper selected for the Best Papers List: 'Adaptive Real-Time Network Monitoring System: Detecting Anomalous Activity with Evolving Connectionist System' at the International Conference on E-Business and Telecommunication Networks in 2005. Additionally, he holds a pending Malaysian patent application (PI 2015700565, 2015) for a method to display large x-ray medical images on portable handheld devices. Key publications encompass 'A dual stream spatio-temporal deep network for micro-expression recognition using upper facial features' (Neural Computing and Applications, 2025), 'SDN-based detection and mitigation of DDoS attacks on smart homes' (Computer Communications, 2024), 'A framework for automatic clustering of EHR messages using a spatial clustering approach' (Healthcare, 2023), 'A Gene-Regulated Neural Network' (International Arab Journal of Information Technology, 2015), 'EFIS: Evolvable-Neural-Based Fuzzy Inference System and Its Application for Adaptive Network Anomaly Detection' (Lecture Notes in Artificial Intelligence, 2006), and 'A Distributed Autonomous Neuro-Gen Learning Engine and Its Application to the Lattice Analysis of Cubic Structure Identification Problem' (International Journal of Innovative Computing and Information Control, 2010). His contributions advance applied machine intelligence in networking and healthcare domains.