I am an applied researcher with Linkedin's Foundational Artificial Intelligence Technologies (FAIT) Optimization team. In my time at LinkedIn, I have worked on a diverse range of topics, including causal inference, large-scale constrained optimization, reinforcement learning and contextual bandits. I earned my PhD in Statistics at Stanford in 2021, advised by Rob Tibshirani. I have a broad range of technical interests spanning data science and AI, but across all of them I like to think about how best to communicate concepts, how to increase the influence these tools have on decision-making, and how to develop easy-to-use software.

I have prior internship experience as a data scientist with the payments organization in Google, and as an applied scientist with and experimentation team in Amazon Search. Before that, I worked in the Singapore Government for 5 years in various roles: a data scientist at IDA Singapore's Data Science Division (now under GovTech), and public policy roles in Singapore's (then) Ministry of the Environment and Water Resources and Ministry of Defence.

I am also an avid blogger! Here are my blogs, in decreasing posting frequency:

• Statistical Odds & Ends: Short posts about concepts and ideas in statistics and related fields which interest me. This is also a place for me to clarify some of my thoughts and pen down notes for future reference.
• Mathematical Odds & Ends: As above, but for math that is non-stats.
• Beyond Solutions: Solutions to math olympiad problems and brainteasers, written with the intent of illuminating the problem-solving process.

My wife, Karen Tay, is doing a lot of interesting work in coaching and consulting through her company Threshold Allies, as well as supporting women experiencing transition and adversity in their work & life journey through Inherent. Check out the links!