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External Research Grants

CY 2024
PromptTutor - Generative AI-enabled Personalised Tutor for Reflection Learning in Programming Courses
Principal Investigator: Ouh Eng Lieh
School of Computing and Information Systems
Funding Source: Ministry of Education Tertiary Education Research Fund
Project Synopsis: 

The objective of this project is to enhance students’ comprehension, retention, and overall learning outcomes in programming by leveraging AI-enabled PromptTutor. It aims to design an AI-enabled intervention that prompts students to reflect on their completed tasks, address doubts in their reflections, and provides additional learning resources in a personalised and timely manner.

CY 2024
Understanding Emerging Trends of Care Communities for Singapore Residents Aged 50 - 76
Principal Investigator: Paulin Straughan
Centre for Research on Successful Ageing
Funding Source: Agency for Integrated Care
Project Synopsis: 

(This is additional funding to SMU for the existing research project.) 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.

CY 2024
For the Singapore Green Finance Center to boost impact investment development in Asia through research, convening and community of practice building
Principal Investigator: Liang Hao
Sim Kee Boon Institute for Financial Economics
Funding Source: Ford Foundation
Project Synopsis: 

This two-year research project aims to provide a framework for measuring, valuing and reporting environmental and social impacts in impact investing, leveraging the Impact-Weighted Accounts Framework (IWAF) that SGFC has been co-developing with other academic and industry partners. It will also demonstrate how the IWAF can be applied to Asian organisations through pilot studies with companies and financial institutions in Singapore and China, and build an impact finance database that aligns with other similar initiatives in North America and Europe for future academic research.

CY 2023
Development of Secured Components & Systems in Emerging Technologies through Hardware & Software Evaluation
Principal Investigator: Gao Debin (SMU Co-Lead)
Centre on Security, Mobile Applications and Cryptography
Funding Source: Cyber Security Agency of Singapore and National Research Foundation, Singapore
Project Synopsis: 

In the past decade, mobile devices and Internet of Things (IoT) have become prevalent in our daily lives, both in business and social settings. The applications of such devices have also been growing exponentially due to the development of technologies that support artificial intelligence (AI) and cloud computing. The advances of cloud and mobile computing in the past decade have fundamentally reshaped the computing infrastructure used by individual, business, and government users into a distributed, heterogenous and collaborative system. Modern applications are hence often built as a fusion of data, software, and services from a mixture of stakeholders. Growing with this evolution are the deep-rooted security concerns over a broad spectrum of issues such as leakage of private data, infringement of software copyrights, and corruption of computation results. 

This research programme gathers a core team of experts from the Nanyang Technological University (NTU) and the Singapore Management University (SMU) to tackle these security concerns. The SMU team aims to holistically address security challenges in the mobile and cloud computing ecosystem pivoting on the new so-called "confidential computing" techniques featuring hardware-based Trusted Execution Environments (TEEs). The research outcomes are expected to build up the infrastructure and capabilities towards a zero-trust computing domain for industry and government users.

CY 2023
Developing a risk assessment and communication platform to translate climate projections to policy
Principal Investigator: Terry Van Gevelt
College of Integrative Studies
Funding Source: National Research Foundation's Climate Impact Science Research (CISR) Programme Grant Call 1
Project Synopsis: 

Singapore's latest high-resolution climate change study, V3, led by NEA/CCRS can simulate future impacts of climate change under different scenarios. Climate change effects are complex and often uncertain in when they are likely to occur and how impactful they will be. Furthermore, it is challenging to engage with climate projections as future climate change impacts seem far removed from our immediate experiences.

Through this project supported by the NRF and NEA under the CISR funding initiative, the research team will map climate projections impacting Singapore into a risk assessment framework that will identify potential policy solutions to reduce future climate impacts and risks. Immersive virtual reality narratives will be constructed to operationalise the risk assessment framework and communicate the future impacts of climate change, along with the solution space, to policymakers and other stakeholders. Taken together, this will make the impacts of climate change directly relevant and provide a platform to translate climate science into effective policy.

CY 2023
AntiGen: Safeguarding Artistic and Personal Visual Data from Generative AI
Principal Investigator: He Shengfeng
School of Computing and Information Systems
Funding Source: AI Singapore's AI Governance Research Grant Call
Project Synopsis: 

In this digital age, advancements in artificial intelligence (AI) have brought about both great opportunities and significant challenges. One of these challenges revolves around the protection of personal data, particularly digital images, which can be exploited by AI technologies. The proposal focuses on addressing these issues by developing solutions that can safeguard the digital rights of individuals and protect their creations from potential misuse by AI technologies. It offers a 'cloak of invisibility' to your digital images, rendering them unexploitable by AI while retaining their visual appeal for human observers. The project aims to return control to the individuals, ensuring the protection of their art and their privacy in the digital world. 

This research/project is supported by the National Research Foundation, Singapore under the AI Singapore Programme (AISG Award No: AISG3-GV-2023-011).

CY 2023
Titan Code Analysis: Vulnerability Discovery with Large Code Models
Principal Investigator: David Lo
Centre for Research on Intelligent Software Engineering (RISE)
Funding Source: Smart Nation Group's Translational R&D 2.0 Grant (TRANS2.0)
Project Synopsis: 

This project involves research and engineering effort to build an intelligent vulnerability discovery system, and to secure citizen data by addressing vulnerabilities in Government software and Digital Government services.

CY 2023
Tokenized Economy and Collaborative Intelligence for Web 3 Media Industry
Principal Investigator: Zhu Feida
School of Computing and Information Systems
Funding Source: Zeasn Technology Pte Ltd
Project Synopsis: 

ZEASN Technology is a global leader in smart TV solutions since 2011, and it is headquartered in Singapore with a strong global presence. ZEASN's flagship product, Whale OS, powers 90 million devices globally for over 300 brands. The collaborative research between SMU and ZEASN Technology Pte Ltd is dedicated to developing an advanced Web 3.0 creative media content ecosystem. Emphasizing critical aspects like tokenomics, incentive design, and privacy-enhancing computation, the project’s our primary goal is to construct a future-proof digital framework that is user-friendly, secure, and maximizes user participation, privacy, and profit. Anticipated outcomes include a robust, efficient, and scalable Web 3.0 creative media content ecosystem, maintaining user privacy while fostering a dynamic, tokenomics-driven creative space. This comprehensive approach seeks to revolutionize how creative media is created, shared, and monetized, empowering users and content creators in the digital era. Leveraging combined expertise from economics, computer science, and digital media, the team we aim to design an ecosystem aligned with the values of the Web 3.0 vision: decentralized, user-centric, and privacy-preserving. An early harvest of this collaboration is addressing key challenges in the century-old film industry, with plans for a Web3-powered virtual cinema on ZEASN's worldwide Whale OS CTVs, aiming to decentralize film distribution and monetization in a transparent and rewarding fashion.

CY 2023
Data-driven Optimisation and Artificial Intelligence for Future Fintech
Principal Investigator: WANG Hai
School of Computing and Information Systems
Funding Source: Tokka Labs Pte Ltd
Project Synopsis: 

The global fintech landscape is undergoing a pivotal shift at its core, driven in part by advanced AI techniques. This project aims to: (i) understand the inner workings of diverse investment systems to assess their transaction patterns; (ii) create algorithms that decode fintech data, offering insights and aiding in market behavior predictions; and (iii) leverage optimization and AI methods to enhance trading and transaction systems.

CY 2023
Sensors In-Home for Elder Wellbeing (SINEW)
Principal Investigator: Tan Ah Hwee
School of Computing and Information Systems
Funding Source: Sengkang General Hospital Pte Ltd
Project Synopsis: 

This project, led by A/Prof Iris Rawtaer (SKH) aims to utilise multimodal sensor networks for early detection of cognitive decline. Under this project, the SKH and NUS team will oversee the project operations, screening recruitment, psychometric evaluation, data analysis, data interpretation, reporting and answer of clinical research hypotheses. The SMU team will collaborate with SKH and NUS to provide technical expertise for this study by ensuring safe implementation and maintenance of the sensors in the homes of the participants, provide the sensor obtained data to the clinical team and apply artificial intelligence methods for predictive modelling.