Events
Future of Innovation
EPD Distinguished Lecture Series & Innovation Forum in partnership with The James Dyson Foundation – Join us to explore how innovation, technology, and engineering are shaping our future.
Ling Chun Kai (National University of Singapore) – Learning and Solving Games in the Presence of Teams
Warut Suksompong (National University of Singapore) – Weighted Fair Division: Additive Preferences and Beyond
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.
Congratulations to Associate Professor Liu Xiaogang’s PhD Student in winning the Royal Society of Chemistry (RSC) Excellent Student Award
He was honored with the “Winner of RSC Excellent Student Award” by the Royal Society of Chemistry (RSC) this September. This award recognizes his academic excellence in leveraging computational chemistry to facilitate interdisciplinary research and his contribution to promoting diversity, equity, inclusion, and respect (DEIR) within the scientific community.
DH Asia Webinar Series: “A Sandbox for Humanistic Data Scientists” by Dr. Setsuko Yokoyama
DH Asia Webinar Series: “A Sandbox for Humanistic Data Scientists” by Dr. Setsuko Yokoyama
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.
DH Asia Webinar Series: “Recreating Chinese Mythical Creatures in the Digital Age” by Dr. Kaby Wing-Sze Kung
DH Asia Webinar Series: “Recreating Chinese Mythical Creatures in the Digital Age” by Dr. Kaby Wing-Sze Kung
