Events
Itai Arad (Centre of Quantum Computation) – Tensor networks and the Belief Propagation algorithm
Master of Architecture Information Session for Intake 2025
The SUTD’s Master of Architecture (MArch) programme offers a future-forward professional degree programme, highlighting design and research for sustainability and the digital transformation of the architectural profession. The programme launches the careers of leaders in architecture by emphasizing independent critical thinking in a thesis project, supported by close collaborations with faculty on cutting-edge research.
Utilising large language models for tour itinerary recommendation
ISTD PhD Oral Defence Seminar by Ho Ngai Lam – Planning a tour Itinerary poses a significant challenge for tourists, especially when navigating unfamiliar territories. The computational complexity of tour recommendation further compounds this challenge due to its inherent intricacies.
Immanuel M. Bomze (University of Vienna) – Need to relax – but perhaps later? Reflections on modeling sparsity and mixed-binary nonconvex optimization problems
Fair generative modelling
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.
Ling Chun Kai (National University of Singapore) – Learning and Solving Games in the Presence of Teams
Towards intelligent analytics for smarter animal behavioural analysis
ISTD PhD Oral Defence Seminar by Ong Kian Eng – Understanding and analysing animal behaviours is crucial for gaining profound insights into the health, needs, and overall well-being of the animal. This involves measuring and monitoring factors such as size, growth, poses, and actions. The analysis of animal behaviour holds significant importance in a wide range of domains and industries, such as livestock farming, veterinary sciences, scientific research, ecological and conservation studies.
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.
It's all in the mix: Wasserstein machine learning with mixed features
It’s all in the mix: Wasserstein machine learning with mixed features
Sparsity in text-to-speech
ISTD PhD Oral Defence Seminar by Perry Lam – Neural networks are known to be over-parametrised and sparse models have been shown to perform as well as dense models over a range of image and language processing tasks. However, while compact representations and model compression methods have been applied to speech tasks, sparsification techniques have rarely been used on text-to-speech (TTS) models. We seek to characterise the impact of selected sparse techniques on the performance and model complexity.
