Research

Research

Research Centres in the Faculty of Computing and Information Technology

There are Six (6) research centres in FOCS which serve as the incubator to explore new ideas and research, and to nurture new researchers. Faculty members perform individual research, group research, and collaborative research with individual researcher(s) from other faculties, institutions, statutory bodies or industry partners. Members provide consultancy, testing and analysis services using scientific instruments available in the laboratories based on the stipulated and approved guidelines and charges. Activities include conducting or organizing research projects, consultancy works, workshops, seminars, conferences and any other relevant activities including papers publishing.

1.     Centre for ICT Innovations and Creativity (CICTIC)

Lead by Dr. Lim Yee Mei

2.     Centre for Data Science and Analytics (CDSA)

Lead by Professor Dr. Lim Tong Ming

3.     Centre for Computational Intelligence (CCI)

Lead by Dr. Tew Yiqi

4.     Centre for Internet of Things (CIOT)

Lead by Associate Professor Dr. Lee Wah Pheng

5.     Centre for Computer Networking and Cyber Security (CCNCS)

Lead by Dr. Wong Thein Lai

6.     Centre for Integrated Circuit Research and Development (CICR&D)

Lead by Dr. Poh Tze Ven



Location: FOCS Laboratories, Block B, TAR UC Main Campus

i. Objectives

The objectives of the Centre are to:

  • Conduct ICT related research activities, trainings and workshops for professional development.
  • Serve as an incubator to encourage ICT innovations and creativity among students and lecturers, ultimately to explore new ideas and research, and to nurture new researchers.
  • Encourage entrepreneurial culture among lecturers and students to produce commercial viable product through software development and ICT.
ii. Vision Statement

To become an outstanding ICT Innovations and Creativity Centre by:

  • Organizing ICT activities to promote ICT Innovations and Creativity among lecturers and students.
  • Actively involved in research activities and industrial projects to address the businesses and global issues.
  • Creating innovative, useful and commercial viable ICT products.
iii. Rationale and Research Plan

The use of digital technologies has become a norm nowadays. There is a need to do more research and development to create more innovative and creative digital technologies solutions to enhance the quality of every individual’s life, increase business productivity and promote economic growth for every nation. There is also a need to produce more ICT and Computer Science talents as well as more technopreneurs to head towards digital nation and support the ICT ecosystems.

Research plan for Centre of ICT Innovations and Creativity is mainly to work with collaborative partners (IHLs or industry) to conduct further research and development in the area of computer science and ICT as listed below (not an exhaustive list):

  • Software Development which includes web and mobile platforms
  • Software Engineering
  • Interactive Software
  • Augmented Reality and Virtual Reality
  • Game Development

To produce innovative, creative and commercial-viable products/technologies and to promote technopreneurship.

iv. Research Centre 

Research Centre Leader – Dr Lim Yee Mei

There are 3 research groups and 1 entrepreneurial support centre within CICTIC:

(a) Product and Platform Development Group

This research group aims to develop commercial viable or innovative product/platform by tapping on the synergy of academia-industry collaboration; and to provide the base or foundation for possible research work under relevant research groups/centres.

(b) IBM Technologies Research Group - IBM Centre of Excellence

This research group aims to nurture specialized human resources to meet the demands of the industries, and to add value to students and lecturers’ skill-sets via professional development workshops/trainings and research work using IBM related technology.

(c) IBM-FASC Entrepreneurial Support Centre

This centre with close collaboration with IBM Technologies Research Group-IBM Centre of Excellence aims to incubate innovative ideas using IBM technologies by TAR UC students, staffs, alumni or SME/SMIs and to carry out entrepreneur and incubator programs incorporating IBM Technologies (where appropriate) with the objective of producing technopreneurs.

(d) Metaverse and Interactive Software Research Group

This research group aims to provide a platform for research and development in the area of multimedia, mix reality and interactive software to develop commercial-viable products with close collaboration with the industry and academia.

v. Achievement in the past 10 years

• MoU between Innotech 360 Sdn Bhd in 2011 for the collaboration in the area of Virtual Reality project via course assignment
• Collaboration with companies to provide real life projects for Final Year Project from time to time
• MOA signed between TAR UC and Easyjoy Entertainment Sdn Bhd in 2015 to develop Bus Tracking System. Beta Launch of TARC EzRide App in 2017
• MOA signed among TAR UC and UMCH Technology Sdn Bhd, SAS Alumni acting through FASC in 2015 to develop Fitness App
• FOCS Symposium to promote innovation and entrepreneurship among students, get students to pitch to the industry.

Location: Big Data Analytic Centre, Block SA, TAR UC Main Campus

i. Objectives

This Centre for Data Science and Analytics (CDSA) aims to establish Tunku Abdul Rahman University College (TAR UC) as the leading centre for big data research and development in Malaysia and in the Asia Pacific region. The centre aims to provide Big Data infrastructure and Big Data Analytics computing resources to collect, manage, filter and generate usable large data sets in order to provide insights to identify patterns, trends, perceptions, prediction and forecast to make good decisions for business and scientific activities.

ii. Vision Statement

To be the leading research centre in Big Data Analytics (BDA) research and development for academics and industry to generate higher productivity, accurate and reliable insights in Malaysia and the Asia Pacific region.

  • To foster academia-industry collaboration in big data analytics.
  • To generate research activities centred on problems specific to Malaysia and the Asia Pacific region.
  • To develop big data solutions with scientists and practitioners from various disciplines.
iii. Rationale and Research Plan

Rationale

 The rationale of setting up the centre is to support activities in the area of big data by collaborating with researchers from interdisciplinary area of studies. Initial collaboration will be with researchers from withtin TAR UC faculties such as FAFB, FCCI etc. Simultaneously, the centre will also intensify academic-industry research and development activities. The centre will provide talents, guidance, and expertise in the technical field of big data to final year project undergraduate student. Meanwhile, the lab established by the centre will also provide R&D resources to postgradaute candidates to explore ground breaking research activities. These projects will be supervised by Professors and academics from the centre. The most important goal of the centre is to research and develop industry-driven systems for the better good to the nation and society. Furthermore, BDA research outcomes can be filed for commercial intellectual property (IP). Any income generated from commercial interests such as licensing and computer applications can be used to supplement the university college’s income and to provide a self-sustainable lab.  In return, researchers will earn their reputation and be rewarded from income generated.

Research Plan

The Big Data Analytics (BDA) Lab established by the Centre for Data Science and Analytics provides four (4) key components: Big Data Solicitor collects real time data streams, Big Data Hadoop (Multi-Node) Cluster, Modelling Servers and Big Data Visualization. BDA is capable to provide essential computing resources for Big Data related teaching and learning needs for undergraduate as well as postgraduate programmes. BDA is able to undertake industry driven research projects to design and develop proof-of-concept prototypes prior to production grade deployment. The centre is designed to be able to provide multi facets cross interdisciplinary research projects. They include projects such as Smart Campus, Agriculture 4.0, Industry 4.0, Education 4.0 and national level Big Data related activities.

The Centre is tasked to produce postgraduates that are skillful in the area of Big Data Analytics. A group of high profile researchers in several selected research directions will be take part in the Big Data related activities to produce solutions for the industry collaborators. In this effort, the Centre at TAR UC will intensify the generation of Big Data Analytics expertise as a talent pool for the industry. At the same time, the Centre for Data Science and Analytics will strategically produce patents and commercialize Big Data related solutions and licenses to generate income. Researchers and students in the area of Big Data will be encourage to setup start-up companies as part of the entrepreneur and incubation agenda of the UC. TAR UC tasks the Centre to take up research projects that will be undertaken by academics and industry to close the gaps found in the industry, business and scientific communities so that the process of solutions design promote mutual, cross-learning between the academics, students and the industry practitioners.

iv. Research Centre, Research Group Leader and Members

Research Centre ChairProfessor Dr Lim Tong Ming

Big Data is the oil of the decade. Farris (2012) and The Economist (2017) claimed that oil of the new digital economy is no longer crude oil but its data. With the advancement of Artificial Intelligence (AI), compact and powerful mobile equipment such as cell phones and wearable devices, social media platforms such as Facebook, Twitter and blogosphere sites and Internet of Things (IoT) like sensors and detectors are driving data complexity, new forms and sources of data. Big Data analytics is the use of advanced analytic techniques such as deep learning algorithms: deep neural networks, deep belief networks and recurrent neural networks on very large and diverse data sets of many petabytes. These data are structured (such as tables in Oracle databases), semi-structured (such as CSV and JSON that are not stored in RDBMS) and unstructured data (such as e-mail, twits, social media messages, documents, videos, photos, audio files, presentations, blogs and web pages), from multiple sources in different sizes to yield insights for planning and decisions. These data are always generated in real time.

Big Data is a term applied to data sets with low-latency whose size or type is beyond the ability of traditional relational databases to capture, manage, and process. In addition, it has one or more of the following characteristics – high volume, high velocity, high variety, high veracity and high complexity.

Analyzing Big Data allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or unusable. Using advanced analytics techniques such as text analytics, machine learning, predictive and prescriptive modelling, data mining, statistics, and natural language processing, businesses and scientists are able to analyze previously untapped data sources independently or together with their existing enterprise data to gain new insights resulting in better and faster decisions.

There are four (4) research groups in CDSA:

(a) Text and Sentiment Analysis Group

Research Group Leader – Dr Lim Yee Mei

Members Professor Dr Lim Tong Ming, Dr Yu Yong Poh, Lim Kong Hua and Kathleen Tan Swee Neo

Location: Big Data Analytic Centre, Block SA, TAR UC Main Campus

Text analytics is the process of analyzing unstructured text, extracting relevant information, and transforming it into useful business intelligence. Sentiment analysis determines if an expression is positive, negative, or neutral, and to what degree. In other words, text analytics studies the face value of the words, including the grammar and the relationships among the words. Simply put, text analytics gives you the meaning. Sentiment analysis gives you insight into the emotion behind the words.

The research group is currently focus on text analytics and sentiment analysis. The group is solving difficult research issues such as social media message that are composed in Chinese, Malay and English across multiple industry domains (F&B, Fashion, Politics and Cosmetic). The group has put an effort to extend lexicons for multiple domains by adopting SenticNet, WordNet and WordNet-Affect. The research outcomes produce useful users’ sentiment, latent topics, fake news or deception detection from customer data. They are critical components of a successful customer experience management for businesses.

(b) Web Mining Group

Research Group Leader – Dr Ng Choon Jin

Members– Professor Dr Lim Tong Ming and Lee Seah Fang

Location: Big Data Analytic Centre, Block SA, TAR UC Main Campus

Web mining is a data mining technique for discovering patterns on the Web. There are three sub-disciplines in Web mining: Web usage mining, Web content mining, and Web structure mining. Web usage mining is the process of mining usage patterns from web data such as the user access patterns. Web content mining, sometimes called web text mining, involves mining the content of a web page so as to discover useful information or knowledge. Finally, Web structure mining is the analysis of the structure of nodes and connections of a web site. It involves mining either the relationships between web pages containing hyperlinks or the structure within a web page document.

Currently, the Web Mining group is working on two fronts. First, the group is working on techniques for mining websites of commercial interests.  Commercial websites can exist in various layouts and formats. This poses problems on large scale data collection from such websites. Second, websites with various layouts and designs can either positively or negatively influence the accessibility of a page or, say, its commercial value where the layout may affect the click rate on advertisements. We will examine the use of graph data mining to allow us to identify a set of specific patterns that favorably influence the advertising click rate of advertisement and use these to analyse the likely effectiveness of different web page layouts or their particular features.

(c) Audio, Image and Video Analytics Group

Research Group Leader – Dr Yu Yong Poh

Members Dr Lim Khai Yin

Location: Big Data Analytic Centre, Block SA, TAR UC Main Campus

Image, audio and video analysis include any technique capable of extracting from the data high-level information, i.e. information that is not explicitly stated, but it requires an abstraction process. The group utilizes machine learning techniques and statistical approaches to carry out a lot of industry research experiments. The group experiments industry driven works such as

1. Reveal who are the people in audio recordings said by diminishing background noise and enhancing the conversation.

2. Conduct photogrammetric analysis on photos or videos to determine dimensions of objects and site features.

3. Enhance images and video to better reveal their contents and to develop trial animations and exhibits.

4. Conduct sound level analysis around businesses to determine neighbourhood sound levels.

5. Document physical evidence during site and lab inspections.

6. Surveillance video analysis to aid event analysis and crash reconstruction.

7.Surveillance video processing and enhancement to aid analysis and testifier presentations.

The group is also working on detecting emotion or feeling by analysing audio streaming for support centers in the banks and information technology companies. Understanding multiple languages (for country such as Malaysia) to provide intelligence responses to the customers who communicate at the end of the phone with auto detection of the emotional state of the conversation in progress is critical for many business corporations. This is because businesses believe that getting new customers cost higher than retaining existing customers.

(d) Predictive and Forecast Modelling Group 

Research Group Leader – Dr Lim Khai Yin

MembersDr Yu Yong Poh, Professor Dr Lim Tong Ming, Tan Wai Beng, Jessie Teoh and Choon Kwai Mui.

Location: Big Data Analytic Centre, Block SA, TAR UC Main Campus

Prediction is an estimation of any event happening in the past, present or future. For example, to predict the percentage of house owners buying home insurance. On the other hand, forecasting is always associated with a time dimension in the future. This involves estimation for some specific future duration or over a period of time. For example, to forecast the total sales in July, 2017 for Apple. Forecasting is a subset of prediction. This research group uses and experiments by proposing and designing models based on structured and unstructured data from the sensors of machines such as CCTV and corrugators of production lines and social media data such as Facebook and Instagram to recommend and provide insights for faster and accurate decision making process. The group will use R, Python, KNIME, and Rapidminer to program and construct predictive and forecasting models, analyse model outcomes, evaluate and measure models’ performances and storytelling the outcomes against the goals of projects for users in the business and scientific communities. Combination of supervised and unsupervised machine learning and statistical approaches will be considered and evaluated. Fusion of structured data set and unstructured social media transformed variables will be correlated and studied to determine their importance in order to explore in the models to be developed. The group is working on digital marketing and social media listening companies since the setup of group in the Centre.

(e) Statistical Analysis and Survey Group 

Research Group Leader – Mr Wong Kok Yong

MembersMr Chee Keh Niang, Ms Lee Shu Gyan, Ms Fong Wai Sham, Ms Chong Voon Niang, Ms Yap Saw Teng, Ms Loo Bee Wah, Mr Chong Kam Yoon, Dr Christopher Lazarus (Sabah branch), Dr. Lim Hong Chang (Johor branch), Ms. Tan Peck Yen (Johor branch), and any interested relevant academic staff who may be appointed from time to time.

Location - Laboratory with SPSS software, Block B, TAR UC main, branch campuses.

This research group conducts research related to theory and application of data science and statistics; provides support and infrastructure to its members for solving data centric and data intensive research problems; and provides consultancy and quantitative analysis service to other education or research institutions as well as for the industry and conducts trainings and workshops. This group’s vision strives to become a reputable, well trusted statistical research and consultancy unit, whose service is well sought after by industries, commercial firms and other organisations of the community.

The group plans to

  • conduct research related to theory and application of data science and statistics, provide consultancy and quantitative analysis service, including statistical analysis and survey, to industries and community
  • provide opportunity for staff to apply their knowledge and skill to practical real life problems.
  • provide opportunity for staff and students to enhance their knowledge and skill through experiential learning.

The group will offer an integrated, comprehensive statistical consulting service covering all aspects of a quantitative research project ranging from the initial study design through to the presentation of the final research conclusions. The Centre will work cooperatively with other established centres across the University College and also conduct research on social, economic and political issues using survey data from large, representative national samples.

v. Industry Projects
  • Digital Marketing Analytics in Sentiment and Text analysis & Advertisement Impact Measuring Predictive Modelling, WebQlo Sdn Bhd, 2018-2019 (Work in Progress)
  • Social Media Listening Analytics, Zanroo Sdn Bhd (In Discussion), 2018-2019 (In Discussion)

Location: FOCS Laboratories B101, Block B, TAR UC Main Campus

i. Objectives

The objective of the Centre is to:

  • explore on designing algorithm and techniques that close to the human’s way of reasoning, i.e. utilizes inexact and incomplete knowledge and performs control actions in an adaptive way. Image and video processing, data mining, natural language processing, artificial intelligence, computer vision processing, robotics and human computer interaction seek the similar goals with Computational Intelligence. It is a way of performing like human beings and most of the time heavily used to perform reasoning and decision making processes.
ii. Vision Statement

To research and integrate the nature-inspired intelligence methodologies into the computer systems to address the complex real-world problems.

iii. Rationale and Research Plan

Computational Intelligence stands for a sub-domain of Artificial Intelligence that endows the ability for a computer or machine to learn and perform any intellectual task, similar to a human being. The research work focuses on algorithm aspects in the area of machine learning, deep learning, digital signal processing that includes audio, text, image and video, evolutionary computing, fuzzy logic, addressing the fundamental issues as well as application in the computer vision, robotics, optimization, data mining and artificial life.

The CCI physical working space will be set up at Block B, Room B101 to accommodate with the High Performance Computers at TAR UC, Kuala Lumpur, for the usage of conducting undergraduate and postgraduate students’ projects. This research centre is connected to the I² Hub at CITC via fibre optics connection.The initial plan is shown in the following Four (4) research and operation groups of Artificial Intelligence, Computer Vision Processing, Intelligent Robotics and Human Computer Interaction.

iv. Research Centre and Research Group Leaders 

Research Centre Leader – Dr Tew Yiqi

There are 4 research groups within CCI:

(a) Artificial Intelligence (AI) Group

AI is a general term that implies the use of computer to model and / or replicate intelligent behaviour. AI research focuses on the development and analysis of algorithms that learns and / or performs intelligent behaviour with minimal human intervention. These techniques have been and continue to be applied to a broad range of solution in robotics, e-commerce, medical diagnosis, gaming, mathematics, etc. Specifically, research is being conducted in estimation theory, mobility mechanism, active computer vision and so on.

Research Group Leader and Members:

Research Group Leader – Dr Lim Khai Yin

(b) Computer Vision (CV) Group

CV processing works on the computer-based interpretation of 2D and 3D image data set from conventional and nonconventional image sources. It involves the field of Medical Image Analysis, Visualization, Object recognition, Gesture Analysis, Facial Expression, Tracking and Scene understanding and modelling, etc.

Research Group Leader and Members:

Research Group Leader – Dr Chaw Jun Kit

(c) Intelligent Robotic Group

Robotic research is involved in research pertaining to all aspects of robotic manipulation, controls and developing Socially Assistive Robots. Our primary focus is to engineer robots that can operate and interact with humans in unstructured environment. Furthermore, human motion and models development is focused. The current project is working on capturing elegant human motion, improve the system and robot programming in Python language.

Research Group Leader and Members:

Research Group Leader – Dr Tang Tiong Yew

(d) Human Computer Interaction (HCI) Group

The focus of this research is to present the recent efforts and developments in the areas of interactive systems, with new affordances of the Internet of things and related technologies; emergence of and need for new and innovative ways in which Human-Computer Interaction can support these. Internet of things can be introduced as the concept where objects in our environment, through some new properties, become smart and begin autonomously communicating with each other and humans, through networks supported by interfaces.

Research Group Leader and Members:

Research Group Leader – Dr Aw Kien Sin

v. Achievement in the past 10 years

• Co-Research with FOET lecturer in the area of Micro-Expression Recognition via Fundamental Research Grant Scheme (FRGS)
• Participated in PECIPTA 2017 to showcase Smart Classroom Management and Car Plate Recognition System and won bronze medals
• Working towards the set up of Computational Intelligence Research Lab to support innovative development through undergraduate final year projects, postgraduate programmes to be offered very soon by TAR UC.

Location: Integrated Innovation Hub (I² Hub), CITC and FOCS Laboratories, Block B, TAR UC Main Campus

i. Objectives

Centre for Internet of Things is established as:

  • An ecosystem provide a common platform and infrastructure to support academic and research activities.
  • A testbed for creative and innovative ideas to be tested and able to provide proof-of-concept.
  • Encouraging multidisciplinary teams that leverage unique strengths of different departments, faculties and campuses.
  • Building high quality education programmes for an emerging sectors and fulfill the industries needs.
  • Reinforcing the partnership with local government, private sectors and communities
  • An proven model scalable for solving the bigger and more complex societal problems in a city or nation.
ii. Vision Statement

To build an IoT enabled Smart Campus to improve services, integrate information, enrich teaching and learning.

iii. Rationale and Research Plan

TAR UC is taking initiative to transform the campus into a smart campus. The smart campus is not only able to provide the effective and efficient services, but also able to foster the soft and hard skills of the academics and students. There are many projects and activities which need coordination to ensure their successful implementation in the smart campus by the Centre for Internet of Things (CIOT).

The CIOT is responsible to coordinate the smart campus development projects for I² Hub, campus community, administration processes, academic services and applied and fundamental research projects on cyber physical system and others related to IoT. CIOT also support the technical aspect of IoT products with potential of commercialization.

The CIOT physical working space will be set up in I² Hub at Cyber Centre, to accommodate with the IoT platform and networking infrastructure for the testing and deployment of products developed by students and academics.

iv. Research Centre

Research Centre Leader – Associate Professor Dr Lee Wah Pheng

There are 3 research groups within CIOT:

(a) Smart Education System Group

Project topics include adaptive learning system that enables learning environment for programming class with adapted materials to learners’ pace and performance, educational revision quiz games, intelligent classroom system that develop an interactive classroom using Internet of Things technology, Robot Tutor and Mobile IELTS Listening Test to allow english listening test to be conducted using mobile phone.

(b) Intelligent Community Service Group

Community services consist of administrative automation system (e.g., online form and report builder, data exchanges between online community with authentication), urban mobility improvement (e.g., bus riding system, parking space system, drone live monitoring and campus route map), security and emergency response (e.g., virtual guard system, panic notification and emergency support system). Besides that, the hospitality and event services (e.g., community webcast system, hiring and lodging service system, stuff selling and catering service system, chatbot system for community and inquiry purpose) and electronic commerce with payment gateway features are a part of community service group.

(c) Infrastructure and Platform Group

Several infrastructures are required to facilitate the IOT platform, based on a centralized architecture design. Message Queue Transport Telemetry (MQTT) protocol is explored and examined to provide community grouping engine, worked with all IOT projects management system. Each of the access to this platform requires registration, authentication, continuous software and firmware supports and updates, and visualization via dashboard monitoring at I² Hub.

v. Achievement in the past 10 years

• Collaborate with the industries and all faculties of TAR UC to develop applications that are going to be hosted by I² Hub, which is the heart of all the integrated innovation projects and the projection of the visualization of data via dashboards.
• Launch of I² Hub on 1st Aug 2018, showcasing the existing research and industrial projects related to Internet of Things.

Location: CISCO Networking and Security Laboratories, Block B, TAR UC Main Campus

i. Objectives

The objectives of the Centre are to:

  • catalyse computer networking and cyber security related research activities and encourage innovations and creativity among students and lecturers, ultimately to explore new ideas and research, and to nurture researchers in the field of computer networking and cyber security.
  • conduct trainings and workshops for professional development in the field of computer networking and cyber security.
  • mentor students in the national or international competitions in the field of computer networking and cyber security.
  • bring students and/or lecturers closer to the industry by working closely with the industry to provide real-life industrial exposure and research opportunities.
  • promote awareness on cyber security for various communities through partnerships with private sectors.
  • provide network infrastructure design and setup support or consultancy for third parties (in-house or industry projects, other IHLs, etc).
ii. Vision Statement

Centre for Computer Networking and Cyber Security aspires to be a network infrastructure design support and consultancy service provider, a catalyst for leading-edge research activities related to computer networking and cyber security and a contributor to community awareness and education on cyber security.

iii. Rationale and Research Plan

This centre aims to create a platform for students and lecturers to do research and consultancy work in the area of computer networking and cyber security, and to create interest and provide relevant industrial skills related to computer networking and cyber security among students.

iv. Research Centre

Research Centre Leader – Dr. Wong Thein Lai

There are 2 research groups within CCNCS:

(a) Computer Networking Group

Location: Laboratory B223, B224, B225, B227 and B228, Block B, TAR UC Main campus

This research group aims to create a platform for students and lecturers to do research and consultancy work in the area of computer networking, create interest and provide relevant industrial skills related to computer networking among students.

(b) Cyber Security Group

Location: Laboratory B223, B224, B225, B227 and B228, Block B, TAR UC Main campus

This research group aims to create a platform for students and lecturers to do research and consultancy work in the area of cyber security, create interest and provide relevant industrial skills related to cyber security among students.

v. Achievement in the past 10 years

• Provide train the trainer workshops to academics by TAR UC lecturers who are the CISCO Instructor Trainer Qualified.
• Collaboration with companies to provide real life projects for Final Year Project from time to time
• Train students for computer networking related competitions and achieve outstanding achievement
• TAR UC Internal grant in the area of information hiding from June 2017 to May 2019.
• Prepare students to go for CISCO Certified Network Associate (CCNA) and CompTia Security+ professional certifications before graduation.

Location: D203, D210, Block D, TAR UC Main Campus

i. Objectives, Vision Statement, Rationale and Research Plan

The main aims of the Centre include continuous improvement of the quality of scientific / industrial research, the development of techniques based on research and the latest scientific / industrial discoveries and greater international visibility. This research group aims to focus on researching techniques on the technological development of IC design and development which may include memory software systems in collaboration with academic partners as well as various industry players. Its research will also involve investigation on the electronics (hardware), firmware, application development and associated memory software with the purpose to incorporate into wide spectrum applications.With this in view the centre therefore will:

  • conduct research and training related to embedded systems (hardware and software solutions) and IC design and development.
  • conduct joint-research activities with research institutions / industry partners.
  • provide consultancy to industries and the community by providing solutions to the industrial needs in the stated areas.
  • provide opportunities for staff to apply their knowledge and skills to practical real life problems.
  • provide opportunities for staff and students to enhance their knowledge and skills through experiential learning.
iv. Research Centre, Research Group Leaders and Members

Research Centre Leader – Dr Poh Tze Ven

v. Achievement in the past 10 years

Industrial Project with TAR UC students and lecturer which leads to successful and fruitful outcome:
• Collaborate with Synopsis, Inc. to solve real industry projects
• Recruitment of potential students to involve in industry projects
• Funding of student project assistants.

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FACULTY OF COMPUTING AND INFORMATION TECHNOLOGY
TUNKU ABDUL RAHMAN UNIVERSITY COLLEGE
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