ESD Research Seminar by Arjun Ramachandra – Many applications in power systems, supply chains, and transportation involve uncertain outcomes and optimisation decisions over multiple time periods while requiring high reliability. Joint chance constraints (JCC) enforce strict reliability but are overly conservative, while single chance constraints (SCC) offer flexibility at the cost of performance.

Professor Chua Chee Kai, SUTD’s Associate Provost for Research and Cheng Tsang Man Chair Professor, has been named in the prestigious list of Highly Cited Researchers™ (HCR) for the second year running, alongside Assistant Professor Xiong Zehui from the Information Systems Technology and Design (ISTD) pillar. They were both named under the category of cross-field.

ESD Research Seminar by Hanwei Li – In this study, we partner with Meituan, a leading shopping platform, to develop a real-time, end-to-end coupon allocation system that aims to maximise customer conversion rate (CVR) while adhering to marketing budgets, addressing challenges of uncertain traffic from a diverse customer base and the need for real-time decision-making.

Congratulations to Assistant Professor Peng Song and Collaborators for Winning the Best Paper Award at SMI 2024

ESD Research Seminar by Liu Xinyu, Cindy – This talk presents rigorous, practical frameworks using continuous-time Markov decision processes (MDPs) and game-theoretic queues.

ESD Research Seminar by Marek Gluza – Dr Marek Gluza will show how the basic aspects of Riemannian geometry of the unitary group such as its curvature, tangent space and dense covering can guide the design of quantum algorithms in this seminar.

Ariel Neufeld (Nanyang Technological University) – Markov Decision Processes under Model Uncertainty

ESD Research Seminar by Antonio Frangioni – Professor Antonio Frangioni will summarise some of the main lines of his research in this seminar, emphasising how he is primarily driven by the desire of solving real-world, difficult optimisation problems.

ESD Research Seminar by Georgina Hall – This talk will demonstrate the usefulness of t-sos submodularity through three applications: (i) a new convex approach to submodular regression, involving minimal manual tuning; (ii) a systematic procedure to derive lower bounds on the submodularity ratio in approximate submodular maximisation, and (iii) improved difference-of-submodular decompositions for difference-of-submodular optimisation.

Congratulations to Associate Professor Lu Wei and his team for their successful launch of new AI Model “TinyLlama”