External Research Grants

Digital wellbeing has arisen in public, governmental and policy discourse as a key measure of a person’s wellbeing through a healthy use of technology. This project aims to identify and measure digital wellbeing for digital readiness, inclusion and safety. Building on the Digital Wellbeing Indicator Framework (DWIF) developed by researchers at the NUS Centre for Trusted Internet and Community, this project will test, evaluate, and revise the DWIF by conducting both qualitative and quantitative analysis of data collected from local context (i.e, Singapore) and global contexts (ie, UK, US, China), with specific focus on mainstream job trends (digital readiness), minority disability access (digital inclusion) and women (digital safety).

This project will develop a new approach, named MINIMA, for protecting end users against privacy and security risks in mobile operating systems. The success of this project can lead to an effective strategy to allow citizens to better protect themselves against cyber threats by minimising their individual attack surface.

The objective of the study is to design automated metrics for evaluating the clarity and readability of judgments and to empirically evaluate how well the judgments written by Singapore judges perform on those measures. Having the ability to define and evaluate judgments on these measures can assist judgment writers (judges and judicial law clerks) to draft clearer and more readable judgments.

A recommender system presents a personalized experience to each user. One perennial issue affecting current recommendation technologies is the sparsity of data related to user preferences. The overall objective of this proposed research is to address this sparsity problem by a combination of approaches that together enable lifelong learning for recommender systems. This is done by allowing the recommendation model to evolve over time to new users and items and, to transfer over to new product categories. In addition, the proposed recommendation model would have the ability to cross from a source platform that accumulates longer-term preferences to a target platform that seeks to integrate short-term signals and reinforcement learning. This provides a system that is able to learn from longer-term preferences and provide the necessary flexibility for cross platform applications.

This research is an ideation/proof of concept project to develop an interactive Web application, called Slide++, which allows students to self-explore additional content related to their courses, while still being directed by the lesson materials provided by an instructor. Importantly, its primary feature is to provide content augmentation for every slide in the form of learning resources relevant to the slide being viewed. These resources can be of various modalities, including Web pages, videos, or questions and answers (Q&A’s).

This project aims to build an Automatic Programming Coaching system that is based on a combination of AI and software engineering techniques to support students practice coding via formative feedback generation.

This project aims to create a 13-week undergraduate elective module to help final-year students achieve one of the graduate learning outcomes of Singapore Management University (SMU): “personal mastery” as a driver of holistic learning in pursuit of both personal and collective well-being. This project will translate the existing program “Mindfulness-based Strategic Awareness Training” for working professionals into the context of tertiary education. Expanding this program to incorporate academic discussion and group work, the course will be the first tertiary-level intervention to combine mindfulness practice with positive psychology to help participants move from suffering to flourishing.

MSE and SMU are collaborating to conduct the Public Cleanliness Satisfaction Survey (PCSS), an annual national household survey that aims to measure and track Singaporeans’ satisfaction and perceptions towards public cleanliness and public hygiene. Findings from the survey will aid in identifying key areas of concern and recommendations which are policy or operational in nature, to improve the public’s levels of satisfaction of public cleanliness, public hygiene and/or public cleaning services.

Rare events, also known as “black swans”, in financial time series can be seen as sporadic and drastic jumps in financial assets returns. Accurate and timely estimates of future risk associated with rare events are of great importance for finance practitioners, policymakers, and regulators. The research team will leverage the most recent developments in quantum-enhanced Monte-Carlo sampling, stochastic modelling and dimensional reduction to design a set of quantum algorithms for rare event estimation that:

1. Enhance the accuracy in estimating the probability of specific rare events – we anticipate a quadratic scaling improvement, where doubling the iterations for the quantum algorithm will result in an accuracy improvement equivalent to a quadrupling of iterations in its classical counterpart.

2. Reduce systematic error caused by dimensional reduction – when constrained to storing the same amount of past data (e.g., macroeconomic indicators), our quantum model can give more accurate rare event predictions than classical counterparts.

This project aims to fill the gap in Asian regionalism and international economic law and policy, through exploring the legal evolution of the ASEAN-Korea trade and investment agreements in light of the ASEAN-Korea Strategic Partnership and Korea’s New Southern Policy, the ASEAN Economic Community Blueprint 2025, the Comprehensive and Progressive Agreement for Trans-Pacific Partnership and the Regional Comprehensive Economic Partnership.