ISTD PhD Oral Defence Seminar by Hong Pengfei – This thesis addresses critical questions surrounding the evaluation and enhancement of reasoning robustness, generalisability, and comprehensiveness in modern language models, particularly under realistic conditions involving noise, ambiguity, domain shifts, and multimodal inputs.

Congratulations to PhD student Hee Ming Shan for obtaining SDSC Dissertion Research Fellowship 2023

ISTD PhD Oral Defence Seminar by Teo Tzu Hsuan Christopher – In this dissertation, we make important contributions in improving fairness in generative models by identifying and addressing constraints which may limit their broader adoption.

ISTD PhD Oral Defence Seminar by Chia Yew Ken – This thesis investigates the crucial role of structured information in natural language processing and artificial intelligence, with a focus on its extraction, utilisation, and extension to multimodal reasoning.

ISTD PhD Oral Defence Seminar by Bhardwaj Rishabh – This thesis investigates critical non-idealities in AI systems, focusing on safety behaviour post-training and alignment.

ISTD PhD Oral Defence Seminar by Dai Siyang – Urbanisation has given rise to increasingly complex systems that sustain and manage the lives of urban residents. As populations grow, the challenges of managing traffic, overcrowding, and environmental challenges escalate. These complexities place stress on urban ecosystems, demanding innovative solutions to ensure smooth and sustainable operations.

ISTD PhD Oral Defence Seminar by Chin Wai Kit Daniel – Social media and social networking platforms have greatly connected people worldwide and democratised information creation and propagation by facilitating seamless and almost instantaneous information sharing between people and communities.

Congratulations to Associate Professor Liu Xiaogang’s PhD Student in Winning the Best Oral Presentation Award

ISTD PhD Oral Defence Seminar by Wang Jiazhao – The increase of the Internet of Things (IoT) has created a complex and heterogeneous wireless ecosystem, demanding IoT gateways that are both flexible and efficient. While Software Defined Radio (SDR) provides the necessary hardware adaptability, its potential is frequently undermined by significant software implementation challenges, including a lack of portability across platforms, prohibitive design complexity for advanced algorithms, and poor computational efficiency. This thesis posits that these persistent bottlenecks can be overcome by a paradigm shift in physical layer (PHY) design: reframing core communication functionalities as learnable, interpretable neural network (NN) models.

ISTD PhD Oral Defence Seminar by Yeo Shun Yi – In this dissertation, PhD candidate Yeo Shun Yi will examine how reflection can be systematically supported through interface interventions to enhance the deliberative quality of user contributions.