Hanan Ather
I am a Member of Technical Staff at the Centre for AI Research and Excellence (CAIRE) at Statistics Canada. I build and deploy AI systems for federal stakeholders, with a focus on evaluation, safety, and security across large language models and agentic systems.
I also develop technical guidance for governing and securely deploying these systems in settings that handle confidential data.
As a member of the Office of Responsible AI, I lead technical reviews of AI systems across government and contribute to frameworks and governance guidance for UNECE, G7 GovAI, and the International Statistical Institute (ISI).
First author of a paper on governing LLM services that handle confidential data, published in Journal of Official Statistics.
Won first place in the 2025 IAOS Young Statisticians Prize for LLM-assisted record linkage, published in Statistical Journal of the IAOS.
Contributed to the development of a United Nations handbook, Uncertainty Quantification in ML-Enhanced Statistical Inference.
Master of Science in Mathematics and Statistics at the University of Ottawa
- Research topic: Deep Reinforcement Learning and Function Optimization
Projects
- I built Probability Lab, an interactive probability and statistics platform currently in use at the University of Ottawa’s second-year engineering program.
- I published a 6-part series of reinforcement learning labs (Jupyter notebooks): Reinforcement Learning Labs.
Graduate Course Notes
Papers & Publications
- Governing Large Language Model Services for Confidential Microdata: A Decision Framework for National Statistical Offices
- LLM-assisted record linkage: A framework for official statistics
- Uncertainty Quantification in ML-Enhanced Statistical Inference — A Practitioner Handbook with Applications in Official Statistics
- Master Thesis: Deep Reinforcement Learning
- Law of the Iterated Logarithm
- MapReduce for Parallel Machine Learning