Work Experience

GovTech Singapore

Singapore

  • Technical Co-Lead (Responsible AI), AI Practice

    – • ongoing

    • Develop Responsible AI tools, methodologies, and best practices for government use - examples include LionGuard, KnowOrNot, and MinorBench.
    • Oversee a team of 3 data scientists and provide technical and strategic guidance for their work - examples include the Responsible AI Playbook, the Responsible AI Benchmark, and LionGuard 2.
    • Work closely with product teams to productionise responsible AI tools (Litmus and Sentinel).
    • Collaborate with key public sector stakeholders on the AI safety, security, and governance issues.
    • Build partnerships with industry and academic experts to jointly work on applied research for Responsible AI, such as Assistant Professor Roy Ka-Wei Lee.

  • Data Scientist, Data Science and AI Division

    – • 11 mos

    • Researched and consolidated MLOps best practices into a MLOps playbook, applying past experiences from working on MLOps in the Ministry of Manpower.
    • Collaborated with two government agencies to test the MLOps best practices and gather feedback.
    • Worked on an internal whitespace project on responsible AI.

  • Forward-Deployed Team Lead, Data Science and AI Division

    – • 1 yr 7 mos

    • Led a team of 3 data scientists to develop data science and machine learning solutions for policymaking, operations, and customer service for the Ministry of Manpower.
    • Contributed to the ministry's data, AI, and data science product strategies.

  • Data Scientist, Data Science and AI Division

    – • 1 yr 6 mos

    • Worked on a variety of data science and policy simulation projects for various public sector agencies.
    • Selected to be part of GovTech's Technology Associate Programme (TAP).

Ministry of Digital Development and Information

Singapore

  • Senior Manager, National AI Group

    – • ongoing

    • Develop governance policies for the use of Generative AI for the entire Singapore public sector.
    • Implement and communicate these policies to public sector agencies, ensuring compliance with the policies while maintaining the public sector's ability to innovate and use AI effectively.
    • Work on AI governance workstreams relating to AI safety and security issues.
    • Deliver training and workshops on AI governance to public sector officers.

Lovelytics

Washington D.C., U.S.A.

  • Lead Data Scientist

    – • 1 yr 1 mo

    • Led product development for machine learning solutions and products for the company.
    • Worked on various projects with external clients (such as the World Bank and FTI Consulting), including custom API integration, Tableau extension development, and geospatial data analysis.

Research & Publications

AI Safety

Measuring what matters: A framework for evaluating safety risks in real-world LLM applications (2025)

Jia Yi Goh, Shaun Khoo, Nyx Iskandar, Gabriel Chua, Leanne Tan, Jessica Foo
Accepted at ICML 2025 Workshop on Technical AI Governance as a spotlight paper
Paper | Slides | Poster

MinorBench: A hand-built benchmark for content-based risks for children (2025)

Shaun Khoo, Gabriel Chua, Rachel Shong
Accepted at ICLR 2025 Workshop on AI for Children
Paper | Poster

A Flexible Large Language Models Guardrail Development Methodology Applied to Off-Topic Prompt Detection (2025)

Gabriel Chua, Shing Yee Chan, Shaun Khoo
Accepted at ICLR 2025 Workshop on Building Trust in Language Models and Applications
Paper | Poster

Safe at the Margins: A General Approach to Safety Alignment in Low-Resource English Languages--A Singlish Case Study (2025)

Isaac Lim, Shaun Khoo, Roy Ka-Wei Lee, Watson Chua, Jia Yi Goh, Jessica Foo
Preprint under review
Paper

LionGuard: A Contextualised Moderation Classifier to Tackle Local Unsafe Content (2025)

Jessica Foo, Shaun Khoo
Accepted at COLING 2025 Industry Track
Paper | Slides

LLM Robustness

Know Or Not: a library for evaluating out-of-knowledge base robustness (2025)

Jessica Foo, Pradyumna Shyama Prasad, Shaun Khoo
Preprint under review
Paper | Slides

AI Governance

Algorithmic Fairness: Challenges and Opportunities for Artificial Intelligence Governance (2022)

Shaun Khoo, Zi En Chow
Published in Singapore Academy of Law Journal Special Issue on AI Governance
Paper

Education

Columbia University

New York, U.S.A.

  • Master of Arts in Quantitative Methods in the Social Sciences (Data Science Focus)

    – • 10 mos

    Courses taken:
    • Data Science: Data Visualization (QMSS 5063), Machine Learning (COMS 4771), Natural Language Processing (QMSS 5067), Modern Data Structures (QMSS 5062), Practicum in Data Analysis (QMSS 5052)
    • Research: Data Analysis (QMSS 5015), QMSS Thesis (QMSS 5999)
    • Others: Urban Datascapes (PLAN 6106), US-China Negotiation (INAF 8621)

    Achievements:
    • 3rd place in Columbia University's DevFest 2019
    • Top 4 winner of Columbia Data Science Institute's Data Art Contest 2019

University of Oxford

Oxford, United Kingdom

  • Bachelor of Arts in Philosophy, Politics and Economics

    – • 2 yrs 9 mos

    Obtained First Class grades in Econometrics, Politics of China, and Theory of Politics

    Activities and societies:
    • Oxford Microfinance Initiative
    • Jacari Oxford
    • Oxford University Photography Society

    Leadership and Achievements:
    • President, Oxford Microfinance Initiative (2017-18)
    • President, Oxford University Photography Society (2016)
    • Finalist, OC&C Stratathon 2017 (Oxford)
    • Finalist, Public Policy Challenge 2016 (Singapore)