Deputy Dean (Student Affair And Alumni)
Faculty of Computing and Meta-Technology (FKMT)
Dedicated academic and researcher specializing in Computer Systems, Brain Signal Processing (EEG), Computer Networking, and Technology Enhanced Learning.
Lecturer (DS52)
Since 2011
I am currently serving as the Deputy Dean (Student Affair And Alumni) at the Faculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI). As a Lecturer (DS52) under the Department of Computer Science and Digital Technology (S.K.T.D), I am passionate about nurturing the next generation of technologists and educators.
My academic journey has driven me to explore the intersections of computer systems, networking pedagogy, and the application of artificial intelligence in analyzing brain signals (EEG) and medical imagery. I actively contribute to research in educational technology, evaluating how different learning styles and personality traits interact with modern IT infrastructures.
Electrical Engineering
Universiti Teknologi MARA (UiTM)
Computer Science
Universiti Putra Malaysia (UPM)
Computer Science
Universiti Sains Malaysia (USM)
A multidisciplinary approach bridging computer science theory, educational application, and advanced signal processing.
Advanced computer networking pedagogy utilizing tools like CISCO Packet Tracer to enhance hands-on learning experiences.
Analyzing human physiological signals, specifically brain waves (EEG), to determine learning styles, stress levels, and vigilance.
Designing instructional strategies, improving teaching competency, and integrating ICT effectively in academic curriculums.
Applying AI techniques in data clustering, classification, and evaluating medical images for clinical benchmarking.
Authors: Nazre bin Abdul Rashid, Md. Zahar bin Othman, Rasyidi bin Johan, Salman Firdaus bin Hj. Sidek
Investigating the use of computer network simulation and visualization tools (CISCO Packet Tracer) to address the challenges in teaching TCP/IP network layering and IP configurations to university students.
Authors: Nazre Abdul Rashid (Co-author / Contributor)
Analysis of AI techniques in medical imagery in terms of evaluation and benchmarking, focusing on taxonomy analysis, challenges, and future solutions.
Authors: Nazre Abdul Rashid, Mohd Nasir Taib, Sahrim Lias, Ros Shilawani S Abdul Kadir
A study proposing reliable indicators to detect and analyze cognitive states and learning styles using human physiological signals via Electroencephalography (EEG).
Whether you are a student seeking academic guidance, a researcher looking for collaboration, or an alumni of FKMT, feel free to reach out.
05-450 6607 / 05-450 6690
Bilik TDHEPA, Bangunan IT
Faculty of Computing and Meta-Technology (FKMT)
Universiti Pendidikan Sultan Idris (UPSI)