Events

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

DH Asia Webinar Series: “A Sandbox for Humanistic Data Scientists” by Dr. Setsuko Yokoyama

A key challenge in data-driven decision-making is the presence of estimation errors in the prediction models, which tend to be amplified by the subsequent optimization model — a phenomenon that is often referred to as the Optimizer’s Curse. A contemporary approach to combat such estimation errors is offered by distributionally robust problem formulations that consider all data-generating distributions close to the empirical distribution derived from historical samples, where ‘closeness’ is determined by the Wasserstein distance. While those techniques show significant promise in problems where all input features are continuous, they scale exponentially when categorical features are present. This work demonstrates that such mixed-feature problems can indeed be solved in polynomial time. We present a practically efficient algorithm to solve mixed-feature problems and compare our method against alternative techniques.

Baby Shark Fund Pitch (Term 5 Projects)

DH Asia Webinar Series: “Recreating Chinese Mythical Creatures in the Digital Age” by Dr. Kaby Wing-Sze Kung

The Design Ethics of Autonomous Machines

Congratulations to Assistant Professor Ang Yee Sin for receiving the Young Scientist Award

ASD Grad Show 2024: Öh!

DH Asia Webinar Series: “The Tale of Genji: Where Traditional Research Meets Digital Technology” by Ayano Takeuchi

Adriel Kuek (DSO National Laboratories) – An Introduction to AI in Defence R&D