External Research Grants

This project focuses on creating self-adaptive embodied agents capable of perceiving and planning in dynamic real-world environments, addressing current challenges like hallucinated plans, poor object tracking and inflexible execution. It employs retrieval-augmented planning, fine-grained environment understanding, and adaptive plan refinement using large multimodal models, validated through simulations and real robots in household tasks. Expected outcomes include new methods for adaptive planning and perception, a kitchen activity video dataset, and demonstrations in domestic scenarios, with broad applications in autonomous vehicles and assistive devices. The initiative aims to impact daily living and healthcare, especially eldercare in Singapore, aligning with national priorities to enhance AI leadership and support the Smart Nation agenda.

This proposal presents OMNICON, a comprehensive framework for generating realistic long-term multi-human motions with environmental context. By designing novel motion representations with generative solutions, OMNICON addresses critical challenges in long-term motion generation, multi-human interactions, and motion-with-context synthesis. Designed to advance applications across animation, gaming, virtual reality, and robotics, OMNICON leverages principles from physics and spatial reasoning to produce temporally consistent, contextually adaptive, and socially coherent motion sequences.

This project, conducted in collaboration with HTX, explores the use of Generative AI (GAI) to advance scientific computing and strengthen cloud security and cybersecurity resilience. This project looks to address deep research challenges in building intelligent, domain-specific automation. This is done by leveraging LLMs for computational chemistry, cloud configuration security and developing robust defence strategies to protect AI systems for use in mission-critical settings.

The increasing realism and accessibility of AI-generated and AI-edited videos threaten public trust, information integrity, and digital security. From misinformation campaigns to identity fraud, such manipulated content can cause real-world harm. Current detection systems are limited: they often focus narrowly on facial deepfakes, lack cultural and linguistic diversity, offer little interpretability, and struggle to adapt to new manipulation techniques. Additionally, most systems emphasize passive detection, without offering mechanisms for content traceability or origin verification. This bilateral research project between Singapore Management University (SMU) and Sungkyunkwan University (SKKU) aims to address these challenges by developing an interpretable, adaptive, and globally deployable deepfake detection and protection system, tailored to the languages, dialects, and socio-cultural contexts of Singapore and South Korea. 

This research/project is supported by the National Research Foundation Singapore under the AI Singapore Programme (AISG Award No: AISG4-TC-2025-018-SGKR).

This project examines the global resurgence of industrial policy as a tool for digital transformation, sustainable development, and economic resilience. Focusing on emerging economies such as Qatar, and drawing on comparison and collaboration with researchers in other jurisdictions including Singapore, it highlights how industrial policy is reshaping trade and investment in an era of technological and geopolitical change.

Singapore and New Zealand both use interRAI, a standardised assessment tool that supports the care of older adults. While interRAI is reliable and effective, integrating Artificial Intelligence (AI) presents a transformative opportunity to enhance healthy ageing and support older people to live longer, more independent lives. Our project brings together clinicians and researchers from the University of Otago, Singapore Management University, University of Canterbury, and University of Auckland. We will identify how to effectively integrate AI into the interRAI assessment, risk prediction, and care planning process to improve efficiency, consistency, and personalisation of care. We will achieve this with a three-pronged approach: 1. AI-assisted Assessments: By partially automating the currently manual interRAI process, we can reduce assessment time by 50% while improving accuracy. We will integrate structured health data and multimedia inputs to generate enriched assessments. 2. AI-enhanced Risk Prediction: We will develop predictive models for outcomes such as fracture risk, cognitive decline, and depression. These models will be embedded into interRAI software to support timely, targeted interventions. 3. AI-driven Personalised Care Plans: We will create dynamic, user-friendly care plans using a knowledge-based AI system enhanced by large language models. These plans will be tailored for patients, families, and clinicians, ensuring clarity and actionable guidance. With support from New Zealand’s Health NZ and ACC, and Singapore’s Agency for Integrated Care, Kwong Wai Shiu Hospital, NWC Longevity Practice, and 59 Socio-Techno Ventures, this initiative will augment existing systems to deliver scalable, cost-effective improvements to aged-care while growing our respective AI sectors. 

This research/project is supported by the National Research Foundation, Singapore under its AI Singapore Technology Challenge – Leveraging AI for Healthy Ageing (AISG Award No: AISG4-TC-2025-015-SGNZ). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.

SMU Yong Pung How School of Law (YPHSL) and Tax Academy of Singapore announced the establishment of the Singapore Tax Academy Research Initiative (STARI) which will be undertaken by YPHSL’s Centre for Commercial Law in Asia. Supported by a grant from the Tax Academy of Singapore, this initiative aims to both contribute to the international tax academic community and serve the body of tax professionals in Singapore through three main streams of work: 1) conduct world-class international tax research; 2) develop local academic capacity in taxation; and 3) build links with international thought-leaders in taxation.

Mild Cognitive Impairment (MCI), a precursor to dementia, offers a chance for intervention to delay dementia onset and facilitate advanced planning. In our ongoing project Sensors In-home for Elder Wellbeing (SINEW) with Sengkang General Hospital (SKH), we have the first longitudinal cohort in Asia from which clinically meaningful behavioural and digital biomarkers are captured with consumer-grade low-cost sensors installed in the homes of older adults. We have also successfully demonstrated proof-of-concept using sensors and machine learning to obtain digital phenotypes for accurate classification of MCI in a home-based setting. In this SINEW+ project, we shall build on the SINEW cohort to validate and refine our explainable predictive modelling approach for early detection of MCI. By leveraging advanced AI models and multi-modal data, we aim to implement and evaluate these solutions in real-world community settings, focusing on their cost-effectiveness and scalability to ensure broad adoption.

The increasing availability of large language models (LLMs) presents opportunities for the judiciary to enhance data accessibility while maintaining confidentiality. This study evaluates whether current-generation LLMs can reliably and safely anonymise judicial data, such as court decisions and case files, to facilitate controlled data sharing for research, legal technology development, and transparency.

(This is additional funding to SMU with a project extension.)

This research project aims to study the working preferences of older Singaporeans and understand their perceptions towards upskilling, reskilling and the types of employment that may be meaningful for them. The results from this research are expected to shed insights and inform the design of a jobs-skills-learning recommender, the SkillsFuture Career Transition Programme (SCTP) and other services and facilities catered to older adults’ needs.