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

ISTD PhD Oral Defence Seminar by Jiaxi Li – Foundation models have demonstrated strong reasoning capabilities, yet their behaviours can vary substantially depending on how learning signals are constructed and exposed during training.

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.

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 Hu Zhiqiang – This thesis advances the computational understanding and manipulation of text styles
through three interconnected pillars: (1) Text Style Transfer (TST); (2) Authorship Attribution (AA); and (3) Authorship Verification (AV), determining whether two texts share the same authorship.

Congratulations to Srilalitha Gopalakrishnan, ASD PhD candidate, for her appointment as President of the Singapore Institute of Landscape Architects (SILA), 2021-2023

Congratulations to Associate Professor Liu Xiaogang’s PhD Student in winning the Royal Society of Chemistry (RSC) Excellent Student Award

ISTD PhD Oral Defence Seminar by Sai Sathiesh Rajan – This dissertation serves to remind us of the importance of thoroughly testing machine learning models before deploying them as they can cause societal, economical and reputational damage.

ISTD PhD Oral Defence Seminar by Jan Melechovsky – In the modern era, new technology is opening opportunities to help various groups of people around the world. In this thesis, deep learning and audio processing is utilized to target the needs of and develop specific applications for patients with progressive neurological diseases, speakers of non-native English accents, and amateur and leisure musicians and music enjoyers.