Research Grants
My research has been generously supported by the Singapore National Research Foundation (NRF), the Ministry of Education (MOE), AI Singapore, and the CREATE programme among others. The projects below span information theory, machine learning, optimization, sequential decision making, privacy, and trustworthy AI.
≈ S$10.0M
research funding secured
21
grants since 2014
4
current projects as PI
2
major NRF awards: Fellowship and Investigatorship
Current Research Grants
Fundamental Limits of Language Models via Information Theory NRF Investigatorship Jul 2026–Jun 2031 S$2,846,450 Online Optimization with Egalitarian and Fairness Constraints MOE AcRF Tier 2 Jan 2026–Dec 2028 S$483,740 Adversarially Corrupted Reinforcement Learning with Human Feedback MOE AcRF Tier 1 Jan 2025–Dec 2027 S$68,000 Part of a CREATE programme with an overall budget of approximately €35 million.
Previous Major Grants
- Learning Latent Structure of High-Dimensional Data with Adversarial TrainingMOE AcRF Tier 2 • Jul 2022–Nov 2025 • S$475,840
- Fundamental Limits for Statistical Learning AlgorithmsNRF Fellowship • Mar 2018–Aug 2023 • S$2,060,000
- Nonnegative Matrix Factorization: Geometry, Privacy and Statistical Lower BoundsMOE AcRF Tier 2 • Jan 2018–Jun 2021 • S$449,340
- Machine Learning, Robust Optimisation, and Verification: Creating Synergistic Capabilities in Cybersecurity ResearchNational Cybersecurity R&D Programme • 2016–2019 • S$379,000
- Network Communication with Synchronization Errors: Fundamental Limits and CodesMOE AcRF Tier 2 • Aug 2015–Jul 2018 • S$500,000
- An Information-Theoretic Understanding of Machine Learning AlgorithmsNUS Young Investigator Award • Jan 2015–Dec 2017 • S$500,000
Complete previous funding history
- Mitigating Security and Privacy Risks of Large Language ModelsAI Singapore Tech Challenge—AI for Security and Fraud Prevention (Singapore–Israel Joint Grant Call) • Nov 2023–Apr 2025 • S$250,000Joint with Tan Nguyen, Gal Chechik, and Biplab Sikdar.
- The Benefits of Active Learning and Testing of Graphical StructureMOE AcRF Tier 1 • Jan 2023–Dec 2025 • S$146,800
- Learning Latent Structure of High-Dimensional Data with Adversarial TrainingMOE AcRF Tier 2 • Jul 2022–Nov 2025 • S$475,840
- Information-Theoretic Limits for Online Learning and Adversarial OptimizationMOE AcRF Tier 1 • Mar 2022–Mar 2025 • S$210,000
- Risk-Sensitive Sequential Learning: Algorithms and Impossibility ResultsMOE AcRF Tier 1 • Mar 2021–Mar 2024 • S$226,000
- On the Relation Between Privacy Metrics: An Asymptotic ViewpointNUS–Berlin Strategic Partnership Grant • Oct 2019–Apr 2021 • S$18,400
- Fundamental Limits for Statistical Learning AlgorithmsNRF Fellowship • Mar 2018–Aug 2023 • S$2,060,000
- Nonnegative Matrix Factorization: Geometry, Privacy and Statistical Lower BoundsMOE AcRF Tier 2 • Jan 2018–Jun 2021 • S$449,340
- Model Selection for Dictionary LearningInstitute of Data Science Grant • Aug 2017–Jul 2019 • S$180,000
- On the Interplay Between Privacy and Statistical InferenceMOE AcRF Tier 1 • Mar 2017–Feb 2020 • S$160,000
- Finite Length Analysis for Multi-User CommunicationNUS–JSPS Grant • Mar 2017–Mar 2019 • S$76,000
- Spectral Methods for Optimization with Applications to RankingMOE AcRF Tier 1 • Mar 2016–Mar 2019 • S$153,500
- Machine Learning, Robust Optimisation, and Verification: Creating Synergistic Capabilities in Cybersecurity ResearchNational Cybersecurity R&D Programme • 2016–2019 • S$379,000
- Network Communication with Synchronization Errors: Fundamental Limits and CodesMOE AcRF Tier 2 • Aug 2015–Jul 2018 • S$500,000
- A Data-Driven Approach to an Improved Understanding of Parkinson's DiseaseFoE–SoC Joint Grant • Aug 2015–Jul 2018 • S$76,000
- An Information-Theoretic Understanding of Machine Learning AlgorithmsNUS Young Investigator Award • Jan 2015–Dec 2017 • S$500,000
- Harvesting and Secure Communication Systems under Finite Delay ConstraintsStartup Grant • Jan 2014–Dec 2017 • S$180,000
Amounts refer to the listed project budgets. For collaborative programmes, the figure shown may refer to the relevant workpackage or joint award rather than funding administered solely by one investigator.
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