This proposal aims to evaluate the efficacy of the Accounting Data & Analytics (AD&A) second major programme offered by the School of Accountancy (SOA) at Singapore Management University (SMU). The AD&A second major programme aims to provide students with skillsets in data and analytics that can be readily applied in the accounting context. Specifically, this proposal seeks to examine (i) the extent to which the AD&A second major programme equip students with key skills and competencies expected in the future accounting workplace, (ii) the extent of the AD&A second major programme achieving its intended learning outcomes and (iii) how the insights gained from this study would impact the design of future programmes (both within and outside of accounting) in data and analytics given the disruption caused by emerging technologies.
Funded by the Ministry of Law, this initiative, known as the Singapore Global Restructuring Initiative, will be housed under the SMU Centre for Cross-Border Commercial Law in Asia, and it seeks to demonstrate international thought leadership on restructuring and insolvency.
This multidisciplinary research project seeks to define and measure a holistic construct of well-being, and identify the factors that impact Singaporeans’ well-being as they progress through the later phases of their life. The research defines well-being as having four primary domains, which are interlinked: social, economic, mental and physical well-being. Leveraging on the Singapore Life Panel®, the research aims to document and better understand which domains of well-being dominate under specific conditions and at specific phases of ageing. This understanding will help in the formulation of targeted interventions that promotes well-being among older adults and thereby advancing successful ageing in the community.
The K-EMERGE research programme, funded by the RIE2020 Advanced Manufacturing and Engineering Programmatic Grant, proposes a knowledge-based AI approach, complemented by advances in deep-learning NLP methods, to address the need for AI systems that are able to perform deep inference for expert-level diagnosis, explanation, instruction, and decision aiding in the context of complex physical systems. As part of the K-EMERGE programme, this project undertaken by SMU aims to develop computational models and technologies for representation, modelling and learning of domain knowledge extracted from text-based technical documents.
This project aims to leverage the Singapore Life Panel® to study older Singaporeans’ awareness and interest of the Advance Care Planning (ACP). Specifically, the project will examine the various sources of information, experience with ACP, as well as intention to officially document their advance care plans in the future.
This research project investigates how transnational judicial training can benefit participating judges and judicial officers. It will also inquire whether and how the delivery of such training to foreign participants can enhance the reputation of the host institution and the host country’s legal system. The research findings will contribute to what we know about incentives to organise or partake in transnational judicial interactions, while also broadening our understanding of the conditions under which transnational judicial education is a promising modality for pursuing such interactions.
Through usage of city-scale commuting data (e.g., public transport records captured by smart card EZLink) to perform multimodal data analysis, this project seeks to answer following questions:
- Question 1: when and where do people commute (related to trip prediction)
- Question 2: how they commute (related to recovery of the exact routes taken by commuters inside the MRT network)
- Question 3: why they commute (related to inference of trip purposes)
A novel parallel framework named CONQUEROR is proposed in this project to support large scale concurrent graph query processing. The framework is built upon the popular heterogeneous architecture, which consists of both CPUs (central processing units) and GPUs (graphics processing units), and they aim to develop a set of novel parallel approaches to fully harness the unique characteristics of the heterogenous platform for processing millions of graph queries concurrently.
As the number of people turning to social media for information and news continues to increase, the spread of fabricated and inaccurate news becomes easier and more common. This has raised concerns about the authenticity of information shared on social media, such that regulators (including China, France and Singapore) have passed anti-fake news laws. This project therefore aims to study whether these laws are helpful in increasing the credibility of information in capital markets, from various stakeholders' perspectives.
This research aims to investigate the characteristics of quantum computing for distributed ledger technologies, which include Distributed Ledgers. Distributed Ledgers are now live and in use and there are many issues and limitations such as in scalability, security and determinism. Areas under consideration for improvement is the consensus mechanism and interoperability between Distributed Ledgers and the aim of this research is to investigate quantum mechanisms for these areas.
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