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ISTD PhD Oral Defence Seminar by Ng Xun Long – Behaviour analysis in complex environments
ISTD PhD Oral Defence Seminar by Ng Xun Long – The thesis presents Chaotic World, a large-scale multi-modal dataset with fine-grained annotations of human actions, interactions, and sounds in chaotic situations.
ISTD PhD Oral Defence Seminar by Pamela Wang – Guided cooperation for multi-agent teams
ISTD PhD Oral Defence Seminar by Pamela Wang – The thesis will study various degrees of centralisation in cooperation mechanisms, spanning from fully centralised planning-based approaches to fully decentralised communicating agents.
ISTD PhD Oral Defence Seminar by Joel Ong – Modern portfolio construction with advanced deep learning models
ISTD PhD Oral Defence Seminar by Joel Ong – We explore the modern application of deep learning techniques in portfolio construction, presenting innovative methodologies that significantly enhance traditional investment strategies. Central to this research are three advanced frameworks that leverage deep learning to optimize financial portfolios.
Congratulations to Professor Zhou Jianying and his visiting PhD Student for receiving the Distinguished Paper Award at ACSAC 2023
Congratulations to Professor Zhou Jianying and his visiting PhD Student for receiving the Distinguished Paper Award at ACSAC 2023
ISTD PhD Oral Defence Seminar by Wang Jiazhao – Neural network-defined physical layer: a new paradigm for software radio in the IoT era
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 Chin Wai Kit Daniel – Explaining graph-based misinformation detection models
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.
ISTD PhD Oral Defence Seminar by Yeo Shun Yi – Designing and evaluating interface based reflection mechanisms to enhance deliberativeness in online deliberation platforms
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.
ISTD PhD Oral Defence Seminar by Qi Zhang – Advancing signal processing with modulo sampling: theory, algorithms, and applications
ISTD PhD Oral Defence Seminar by Qi Zhang – Analog-to-digital converters (ADCs) are crucial in signal processing but face challenges when handling high-dynamic-range signals. In radar systems, the coexistence of strong and weak targets can lead to significant information loss due to ADC limitations.
Congratulations to Assistant Professor Liu Jun and his PhD Student Qu Haoxuan for winning PREMIA Best Student Paper Award
Congratulations to Assistant Professor Liu Jun and his PhD Student Qu Haoxuan for winning PREMIA Best Student Paper Award
ISTD PhD Oral Defence Seminar by Gionnieve Lim – Human-centred design of automated labelling interventions to mitigate misinformation on social media
ISTD PhD Oral Defence Seminar by Gionnieve Lim – The thesis investigates the use of various labelling interventions that incorporate automated fact-checking elements for humans, examining people’s perceptions of the labels and their attitudes to the labelled content.