The domains we are currently pursuing are in the areas of renewable energy and automotive systems. We have in depth technical expertise and conduct research in the areas of audio-visual systems, wireless communications, optical communications, antennas, power electronics, machines and embedded systems.
Why study a postgraduate degree in Electrical Systems and Applied Mathematics at the University of Nottingham Malaysia?
Innovative research: Engage in groundbreaking research that pushes the boundaries of electrical systems and mathematical applications.
Collaborative environment: Work alongside experts from various disciplines, fostering an interdisciplinary approach to problem-solving.
State-of-the-art facilities: Benefit from advanced labs and research centres, equipped with the latest tools and technologies.
Industry relevance: Our research is aligned with industry needs, ensuring that you're working on projects with real-world applications.
Global network: Collaborate with researchers from our UK and China campuses, as well as other leading institutions worldwide.
Our main research groups in the division are:
Applied Electromagnetics and Communications
Research expertise within the Applied Electromagnetics and Communications Research Group includes equalisation and algorithm design and analysis, detection algorithm design and analysis, and matlab based simulations.
- Design and analysis of very efficient near-optimal equalisation and decoding algorithms for broadband wireless MIMO systems
- Reducing the computational complexity of TURBO codes
- Develop new detection algorithms that increase data throughput which are suitable for IEEE standards
- Design of fast convergence blind equalisation algorithms, for both single antenna as well as multiple-antenna systems
- Blind equalisation to eliminate the bandwidth-wasteful training sequence
- Novel combination of space-time-block-codes (STBC) and spatial multiplexing (SM) techniques to increase capacity or effective data throughput
- Simplifying TURBO decoding algorithm
- Design of novel near maximum-likelihood (ML) MIMO detection algorithms with much lower computational complexity than the optimal ML algorithm
The Applied Mathematics Research Group applies mathematical techniques to solve problems in various domains such as mathematics, physics and engineering. Members of our group are actively involved in research in quantum information, quantum field theory, probability and statistics, fractional calculus and asymptotic analysis.
- The Casimir effect
- Statistical analysis of non-parametric estimators
- The Kochen-Specker theorem
- Fractional integrations on discrete time scales
The common thread in the research activities of the Intelligent Systems Research Group is the use of intelligent systems for pattern recognition and machine learning in order to predict an outcome and/or decide on a suitable course of action in engineering and industrial processes. The inference engine used is the Support Vector Machine, a linear classifier with good generalisation capability.
- Pipeline riser defect prediction using Support Vector Machines
- SmartVehicle System to protect drivers and motor cyclists on Malaysian Roads (MOSTI)
- SVM based battery – Super-capacitor energy management system for Electric Vehicles (MOSTI)
- Detection and Prediction of Lung Cancer Using the zNose with the Support Vector Machine Classifier (MOSTI)
- Modelling and Analysis of Maglev Vertical Axis Wind Turbine
Power Electronics, Machines and Control
- Power electronics
- Energy conversion systems
- Renewable energy conditioning
- Regenerative braking/supercapacitor charge storage
- Energy management
- Electric machines and drives
- FACTS and HVDC systems
- Control systems; intelligent, robust, real-time with embedded systems
Graduates from the Electrical Systems and Applied Mathematics division are equipped to take on roles in various sectors, given the interdisciplinary nature of their studies. Potential career paths include:
Electrical Systems Engineer
Systems Control Engineer
Machine Learning Engineer
Energy Management Specialist
Are there opportunities for students to collaborate on faculty research projects?
Yes, students are encouraged to work alongside faculty on ongoing research projects, gaining hands-on experience and insights.
Are there partnerships with industries for research or internships?
Yes. UNM has established collaborations with various industries, providing students with opportunities for internships and practical research.
What kind of support is available for students looking to publish their research?
The division provides mentorship and guidance on research publication, helping students present their work in reputable journals and conferences.
How do the courses incorporate the latest technological advancements, such as AI and IoT?
Our curriculum is regularly updated to include the latest technological trends. Topics like AI (Artificial Intelligence) and IoT (Internet of Things) are integrated into courses and research projects.
How do I choose a research topic or area of specialisation within the division?
Faculty members often provide guidance based on current industry needs, emerging trends, and student interests to help choose a relevant and impactful research topic.
How does the division prepare students for the rapidly evolving tech industry?
Through a mix of foundational knowledge, hands-on projects, industry collaborations, and exposure to the latest trends, UNM ensureS students are adaptable and ready for the dynamic tech landscape.
Are there scholarships available for postgraduate students?