Events

In this talk, we will present a framework on prescriptive analytics that has been successfully applied to several clients’ projects including a major US airline and a large financial institution. The framework consists of a causal teacher model which produces counterfactual outcomes corresponding to different treatment actions, and a prescriptive student model which distills a set of policies that optimizes a given objective in the form of a tree. The prescriptive tree can be built greedily as demonstrated in our ICML 2021 paper. As the greedy heuristic is unable to incorporate constraints that are ubiquitous, in our AAAI 2022 publication, we introduce a scalable mixed-integer program (MIP) approach that solves the constrained prescriptive policy generation problem via column generation.

Social science and humanities research could help overcome these weaknesses. The chapter shows how South Asian culture influences engineering practice and offers suggestions for social science and humanities scholars seeking rewarding research opportunities.

Congratulations to Senior Lecturer Chandrima Chatterjee, who has been recognized internationally as having achieved the status of Fellow by AdvanceHE.

The Fellowship recognizes personal and institutional commitment to professionalism in learning and teaching in higher education. This involved submitting a reflective portfolio of teaching practices, with supportive evidences.

Congratulations to Assistant Professor Liu Xiaogang for receiving the Shimadzu-SNIC Industry Award in Applied and Translational Chemistry 2022!

Mingmei Li & Benjamin Tan (Singapore University of Technology and Design) – Presentations by the Aviation Studies Institute

Congratulations to Senior Lecturer Tan Mei Xuan, who has been recognized internationally as having achieved the status of Fellow by AdvanceHE.

The Fellowship recognizes personal and institutional commitment to professionalism in learning and teaching in higher education. This involved submitting a reflective portfolio of teaching practices, with supportive evidences.

Very often, modern datasets in operations research have a panel structure — we observe data for many of distinct “units”, but for each unit we observe only a handful of relevant data points. As an example, consider a large online retailer where we observe data from thousands of distinct products, but each product typically has only a few sales. The dominant intuition when solving stochastic optimization problems in such settings is that we should “learn from similar units”, e.g., we might use covariates to cluster similar units and pool their data together when solving optimization problems. This intuition (in some form or the other) pervades most modern approaches to contextual stochastic optimization. Conversely, this intuition also suggests that if units are not “similar” in any way, aggregating data can only hurt us and we might as well treat each unit separately.

Assistant Professor Liu Xiaogang together with Assistant Professor Leo Chen Huei’s PhD student, Shanmugham Meyammai, presented their research work titled “Time Dependent Activation of TMAO Induced Apoptosis and Inflammation on Human Microvascular Endothelial Cells” in the Monash-INITIATE 2022 online conference. The research work was done under the supervision of Assistant Professor Leo Chen Huei.

Mey’s abstract was selected for oral presentation, and she won the Third Prize of the Best Oral Presentation Award, Monash Initiate 2022. Congratulations!

SUTD Team won the 2nd Runner-Up Prize in the HPC Innovation Challenge for the Environment competition in September 2022. This competition intends to explore how we can tackle environmental challenges using High-Performance Computing (HPC). The SUTD team, consisting of Miss Wu Xia and Mr. Shen Tianruo, focused on the computation-aided design of “small” and “red” fluorophores (namely ‘Singapore Red”) for bioimaging and biosensing applications. Their computational design minimizes ‘trial-and-error’ in experimental synthesis and thereby reduces waste generation during the development of chemical products. This design-centric approach offers a new route to greening chemical synthesis and reducing carbon emission and waste discharge to the environment.

Both Wu Xia and Tianruo are from the Science, Mathematics and Technology Cluster, supervised by Assistant Professor Liu Xiaogang.

Congratulations to Assistant Professor Liu Xiaogang’s Graduate Students in Winning the HPC Innovation Challenge for the Environment 2022