External Research Grants

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.

The proposed research aims to systematically examine how consumers react toward and interact with AI systems in marketing contexts, in particular recommendations AI (e.g., digital content curator such as Netflix movie recommendation) and conversational AI (e.g., voice assistants such as Amazon Alexa), across Singapore, China, and the US. Insights from the research can contribute toward driving consumer acceptance and adoption of AI systems in Singapore and beyond.

This project will explore the translational politics of smart city knowledge transfer, and how these politics manifest in urban environments throughout Southeast Asia. We define “translational politics” as the (mis)alignments, tensions and opportunities for exploitation that emerge when different scales of influence converge and materialise within a given urban context. We will explore the emergence of “technocratic regionalism” as a strategy through which power and inequality are (re)produced at both the macro (or global, regional and national) and micro (or local) scales.

The development in China's food system (how agriculture production is organized and how urban demand is met) is reshaping the global food system, on which Singapore heavily depends for her food supply. Agricultural and rural change will also powerfully shape the economic development and social stability in China. This project aims to understand the profound changes that are transforming Chinese agriculture and the implications this has to the Chinese society and the global food system.

This study seeks to examine the impact of four communication modes – videoconferencing, audio call, text messaging, and face-to-face interaction – on negotiation outcomes. In addition, the study explores the potential moderating effects of negotiator traits – such as conflict resolution style, communication style and personality type – on the media effects on negotiation. The study’s findings will cast light on the impact that different media have on diverse aspects of negotiation. This research is timely as general preferences towards communication media could have evolved considerably in the wake of the unprecedented reliance on video-conferencing and development of new technology and media.

This project aims to study how better care options can be provided and developed for the local community. The first study will centre around the awareness and preferences of Singapore residents aged 50-76 regarding Assisted Living, with a set of survey questions to be designed and fielded through the Singapore Life Panel. Other focus areas will be developed over the course of this 2-year collaboration based on up-and-coming topics as they emerge.

This project aims to explore the implications of Dhaka's upcoming mass rapid transit (MRT) system and first line, MRT-6, on the distribution of socioeconomic activity and mobility within the city. Even though large-scale mass transit projects like the MRT system affect travel conditions in the entire city and are important for sustainable development, a comprehensive assessment of an infrastructure project is rarely undertaken. Data such as simulated and actual trips, property prices, and job availability will be collected both before and after the start of the line, as well as within and outside the areas directly affected by MRT-6. Analysis involving recent advances in econometric and spatial modelling techniques will be conducted to estimate the general equilibrium impacts of MRT-6 and understand the distribution of welfare gains across space and different socioeconomic groups, as well as the channels through which these gains transpire.

This is a project under the AI Singapore 100 Experiments Programme. It tackles the research challenge of generating good logistics plans and schedules for parcel delivery using AI. uParcel faces the challenges that the number of deliveries daily are in the thousands and the number of drivers delivering a day is in hundreds, which makes it very challenging to match jobs to drivers and encourage job acceptance. Using reinforcement learning coupled with large-scale optimization methods, the research team will develop route optimization, dynamic recommendation, and logistics marketplace matching algorithms for improving operational efficiency. This will also greatly improve city logistics by reducing trips and congestion.