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FICT strives to become a catalyst for the seeding and growth of information and communication technologies research with unique capabilities and contributions that can distinguish themselves from similar groups in other universities. It is also the intention for us to leverage upon and support the particular strengths of the local ICT infrastructure vis-a-vis other economies globally.
FICT serves to build on the diverse strengths of existing faculty as reflected by the research clusters. It will facilitate cooperation amongst these diverse groups, as well as cross disciplinary research collaboration with other faculties and universities.
With the vision of UTAR becoming a worldwide renowned university, FICT spearheads research and innovation work in five main research groups:
Computer vision research group aims to carry out research in the area of:
IoT research group aims to carry out research and development particularly in the area of networking and communication security. Our main focus includes but not limited to the following areas/topics:
The research group focuses on the latest research directions in the domains of software engineering, knowledge management and information systems. The research group mainly conducts research but not limited to the following areas:
Leader: Dr Goh Chuan Meng
Computing in Healthcare group conducts the researches in investigating the needs of healthcare-related infrastructures and technologies. The studies include of:
1. Predictive algorithm in Biomedical Imaging and healthcare
2. Medical imaging equipment and tools
3. 3D modeling and printing
Furthermore, the extent to which the research areas will be explored in the works are as follow:
1. Artificial Intelligence, Signal Processing
2. 3-D Imaging and Visualization, 3-D Printed Modeling Reconstruction, Medical Image Processing
3. 3D Facial Reconstruction, Object Matching/Registration
4. Computer Vision, Image Processing
5. Modelling, Control Theories, Robotics, Biomedical
6. Electroencephalography (EEG), Learning Process
7. Machine Learning, Semantic Web
8. Bioinformatics, Machine Learning, Computational Biology
The sample of the conducting projects are:
• Classification of Thoracic Disease using X-ray image : A multi-instance learning formulation
• 3-D Printed Anatomical Model Reconstruction Simulating Human Anatomy based on Medical Imaging as an Effective
Learning Tool: To construct a low-cost 3D printed knee joint for an effective learning purpose.
• AI-based Predictions in Health & Diseases: To identify set of marker regions that are corresponding to the diseases of interest using computational algorithm.
• Gens-gene Interaction Modeling: To model correlation of a set of candidate markers that are associated to the diseases of interest.
• Development of Detection Method using Neurophysiological Signals for Mental Health Issues: To develop a detection method of mental health issues using EEG-based or fMRI-based data
• Interactive Tool Using Augmented Reality (AR) for Learning Anatomy Based on Medical Images 3-D Reconstruction: To enhance the interaction learning for the medical students with the 3D human body anatomy and the real-time environment using AR technology.
• Prototype Design of Vein Localization and its Depth Estimation in Embedded System: To produce an accurate imaging system for venipuncture purpose.
• 3D Face Reconstruction using Simplified Generic Elastic Model and Deep Learning Method: To improve the appearance of the reconstructed face model.
Leader: Miss. Ana Nabilah Binti Sa’uadi
Education Technology (EdTech) is an industry that has been growing exponentially due to technologies used for educational purposes that keep hybrid classrooms connected. The technologies being used help facilitate collaboration in an active learning environment.
This research group covers the research on the use of tools, technologies, processes, procedures, resources, and strategies to improve learning experiences in a variety of settings, such as formal learning, informal learning, non-formal learning, lifelong learning, hybrid learning, learning on demand, workplace learning, and just-in-time learning.
This research group is also not limited to the following areas:-
- VR-Based (Virtual Reality) and AR-Based (Augmented Reality) Learning
- AI-Enabled (Artificial Intelligence) Education
- Game-based learning (Gamified Learning)
- Asynchronous Learning
- Blockchain Technology
- Learning Analytics
- Cloud Technology
- Education in ICT
- Big Data
The expansion in information and communication technologies will necessitate technical and real-world research that is unique to business needs. FICT is equipped to move in this direction guided by inputs that we obtain from industry, and the research conducted will be in an applied and focused manner so that outputs are usable by the concerned industries.
Universiti Tunku Abdul Rahman (UTAR): http://www.utar.edu.my
Faculty of Information and Communication Technology (FICT): http://fict.utar.edu.my
FICT staff directory: http://www.utar.edu.my/staffDirSearch.jsp?searchDept=FICT&searchDiv=All&searchName=&submit=Search&searchResult=Y
Centre for IoT & Big Data (CIoTBD):http://ciotbd.research.utar.edu.my