I am a Senior Data Scientist at GovTech Singapore. I'm currently the technical co-lead for the AI Practice's Responsible AI team, which focuses on applied research and experimentation for AI safety, robustness, and fairness. Our team has developed and open-sourced several tools, such as LionGuard for localised safety (see version 1 and version 2), KnowOrNot for out-of-knowledge-base robustness, LLM guardrails for off-topic prompts and system prompt leakage, and benchmarks like MinorBench (child safety) and RabakBench (localised safety). We also have a Responsible AI playbook to improve the public sector's technical understanding of key responsible AI concepts and tools.

I am also concurrently a Senior Manager at the Ministry of Digital Development and Information (MDDI), working in the National AI Group to develop AI governance for the public sector. My work spans from developing governance policies and controls for the use of Generative AI in the public sector to implementing and communicating these policies to public sector agencies and officers.

Beyond my work in the public sector, I am also an adjunct lecturer at the National University of Singapore, teaching an undergraduate course on data science and public policy (DSA4264: Sense-making Case Analysis - Public Policy and Society).

Prior to this, I was the data science team lead at the Ministry of Manpower's Co-Lab unit, working on a wide range of data analytics, machine learning, and LLM-related projects to support the ministry's policymaking and operations. Before joining the Singapore government, I was the Lead Data Scientist at Lovelytics in Washington D.C., where I was responsible for the company’s data science projects with external clients.

I graduated from Columbia University in 2019 with a MA in Quantitative Methods in the Social Sciences (Data Science Focus), and from the University of Oxford in 2018 with a BA (Hons) in Philosophy, Politics and Economics.

Last updated on 13 September 2025