Lau Wei Jian( Award Conferred 30 April 2025)
Title of Thesis:‘ Anticipatory and Adaptive Communication Framework for Dynamic Flying Ad Hoc Networks using Artificial Intelligence.’
Drones are becoming an essential part of future robotic systems, especially when many of them need to work together as a team. For these drone teams to operate smoothly, they need a strong and reliable way to communicate with each other. This thesis focuses on building a better communication system for drone networks, helping them share information more effectively- even when flying in dynamic environments without fixed infrastructure. To achieve this, the research introduces a smart, multi-layered framework that improves how drones connect and cooperate using Wi-Fi. It includes new models and protocols powered by advanced techniques, including Artificial Intelligence, to boost reliability before and during flight. The result is a more dependable and efficient drone communication network that can support a wide range of real-world uses- from search and rescue missions to delivery services and environmental monitoring.
Supervisor: Dr Joanne Mun Yee Lim Associate Supervisor: Dr Chong Chun Yong
Reuben Lim Yaw Hui( Award Conferred 9 July 2025)
Title of Thesis:‘ A Reliable Communication Framework for UAV Swarm Networks.’
Unmanned aerial vehicle( UAV) swarms are used in many industries, but reliable communication with ground control is crucial to prevent accidents. Since UAVs operate in changing environments, predicting and maintaining communication reliability is challenging. This study proposes a machine learning-based framework to improve communication stability. It includes signal quality modeling, AI-powered reliability prediction, and a failure mitigation scheme using UAV and ground control rebroadcasting. The approach successfully maintains over 99.9 % reliability in simulations, ensuring safer UAV swarm operations under various conditions. These findings help improve UAV network performance and prevent communication failures in real-world scenarios.
Supervisor: Dr Joanne Mun Yee Lim Associate Supervisor: Associate Professor Boon Leong Lan Associate Supervisor: Dr Patrick Wan Chuan Ho
Jiale Lee( Award Conferred 5 March 2025)
Title of Thesis:‘ Development of Lead-free Halide Perovskite-based Materials for Efficient Photocatalytic CO2 Reduction to CH4.’
This thesis explores the development of lead-free halide perovskites for converting carbon dioxide( CO2) into usable energy. The research focuses on improving photocatalytic performance using various strategies such as mixed halide formation, trivalent metal incorporation, heterojunction engineering, and photosensitiser immobilisation. The results show enhanced CO2 conversion to methane( CH4) under visible and near-infrared light. These findings present a potential solution to reduce atmospheric CO2 levels and offer sustainable alternatives to fossil fuels. The study provides valuable insights into clean energy technologies, which could help mitigate climate change.
Supervisor: Dr Lling Lling Tan Associate Supervisor: Professor Siang Piao Chai
Lim Jia You( Award Conferred 2 April 2025)
Title of Thesis:‘ Single-Pixel Image Reconstruction and Super-Resolution using Deep Learning.’
Single-pixel imaging( SPI) utilizes a single-point detector and modulated illumination patterns to capture images through measurement acquisition and reconstruction. However, existing SPI reconstruction techniques are inefficient due to their iterative nature and high-sparsity sampling patterns. This research develops a deep learning-based model and a novel SPI basis to enhance the imaging efficiency and accuracy of SPI while minimizing computational demands. Experiments show that the proposed super-resolved SPI system can achieve significantly higher imaging resolution and improved accuracy at low sampling ratios in real time and can be readily integrated into more advanced SPI technologies in the future.
Supervisor: Associate Professor Xin Wang Associate Supervisor: Professor Raphael Phan Associate Supervisor: Dr Chiew Yeong Shiong
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