Smart Systems, AI, and Data Science

The onset of the Fourth Industrial Revolution, or Industrial Revolution 4.0 (IR4.0), marks a significant shift in the way industries operate. Already, the convergence of digital technologies, automation, artificial intelligence (AI), and data analytics over the past few decades have had a profound impact on the world and have transformed the most commonplace consumer experiences.

In the context of industry, the marked acceleration of smart cyber-physical system (CPS) capabilities are increasingly transforming traditional manufacturing and industrial processes. This revolution is reshaping industries across sectors, offering opportunities for increased efficiency, innovation, and customisation. However, it also presents challenges related to workforce adaptability, data security, ethics, and infrastructure.

cluster  5-100




Advancing smart integral systems to revolutionise industries

This research cluster is dedicated to supporting the global shift from conventional industrial systems or products to smart integral systems. Our multidisciplinary research aims to leverage the advancements in Internet of Things (IoT) to accelerate and achieve the seamless integration of CPS.

By combining physical processes (such as sensors and machines) with computer algorithms (including artificial intelligence and data science), we aim to enhance efficiency and productivity in various industries. These three critical areas, namely physical processes, computer algorithms, and smart systems, work together symbiotically to revolutionise industrial operations.

Moreover, the cluster will serve as a collaborative platform for research, fostering partnerships with universities and industry partners, both within Malaysia and globally. By promoting collaboration, we can pool resources, expertise, and knowledge to drive innovation and create real-world solutions for the challenges posed by the shift to smart integral systems.



Cluster structure

This cluster consists of eight subgroups, namely: Financial Analytics, Intelligent Manufacturing, Autonomous and IoT Integration, Smart Healthcare, 3D Simulation in Virtual Environment, Data Science, Human Resource Management & Talent Acquisition, and Computer Vision and Machine Learning.

To fully harness the potential of these technologies, multi-disciplinary research is essential. By embracing diverse research initiatives, we can unlock the transformative power of digital transformation and smart CPS, paving the way for a more productive, sustainable, and interconnected future.





Take a Look at Our Work

Smart Systems, AI, and Data Science 1-100

Scenario-based safety testing for autonomous vehicles using Malaysian road and traffic environment

In this project, the team is working on evaluating the performance of autonomous vehicles in Malaysian road and traffic environments using software-in-the-loop and hardware-in-the-loop testing. The project also focuses on the development of a vehicle model and driver prediction model, which are virtually generated. Lastly, the project focuses on the safety assessment for urban driving, which is mainly conducted using collision avoidance systems.

Smart Systems, AI, and Data Science 2-100

Automated microalgae cultivation system development

A joint research project with Algae International Berhad (AIB), this project aims to develop an automated microalgae cultivation system. Utilising AI and data science, this automated system allows the sustainable and efficient production of microalgae on an industrial scale.

Smart Systems, AI, and Data Science 3-100

Paediatric 3D printed mini-tablets

Paediatric patients require age-appropriate medication, as dosages need to be specifically tailored. This makes 3D printing well-suited for paediatric drug delivery, as it allows for more flexibility than traditional tableting. Using additive manufacturing to rapidly design small, clinically acceptable multi-particulate dosage forms, point-of-care treatment would allow more efficient and personalized drug treatment.
We have successfully produced immediate-release mini-tablets containing paracetamol using semi-solid extrusion 3D printing. However, trying to produce a range of tablets and release profiles has caused extrusion issues. The project outcomes now focus on evaluating various pharmaceutical excipients for their future printability, with the goal of developing a guide on excipient selection for 3D printing medicines for pharmaceutical formulators.

Smart Systems, AI, and Data Science 4-100

Unsupervised Learning Study in Financial Crime

A partnership with BAE Systems, this project examines how unsupervised machine learning can be used in the discovery of previously undefined risk, known as “missed risk” in the context of financial crime.

Leveraging the university’s experience in other domains, such as natural language processing and computer vision, the research team will use these datasets to train a machine learning model that can detect financial crime. The goal of the research is to develop a new method that is more accurate and efficient than existing methods.