: this blog
I like to analyze what I do. I track my time and make spreadsheets. Why not write about what I learned?
Last updated: Jan, 2021
I’m a data scientist by trade, where I build machine learning models and infrastructure at scale. Currently I am a principal data scientist in fintech. In my previous role, I developed the company’s very first ML powered website recommender system, deployed to millions of customers, and created a custom OpenAI Gym environment for a reinforcement learning project in production.
I’m a Steering Committee Member (reinforcement learning lead) of Aggregate Intellect (formerly Toronto Deep Learning Series), where we get together weekly to discuss machine learning research and keep up with state of the art in industry. Post-pandemic, we have transitioned to fully online events, and have 12k+ YouTube subscribers. (YouTube channel) (Website)
I enjoy volunteering to give back to the community - you can find me mentoring or speaking at various workshops around Toronto. I have spoken at PyCon Canada, PyCon India, Toronto Machine Learning Series (TMLS), Data Science Conference Europe, and more.
I’m also an indie game developer, having showcased my game in Bit Bazaar and Damage Camp, both gaming conferences held in Toronto. The game has also been mentioned on PC Gamer, Destructoid, and other major gaming news sites.
I’m a 2-time speaker at Visual;Conference where I shared my knowledge on marketing on Steam as an indie dev, as well as my game development pipeline.
In a bit of a cross-over between these two fields, you can find me yearly at the Game Developers Conference in San Francisco (Thanks, DMG!), and am part of the AI Roundtable: Expert session.
Formal education wise, I hold a master’s degree from University of Toronto, and bachelor’s from University of Waterloo.
I love what I do, and what gets me up every day is that I have much, much more to learn!
Disclaimer: This blog represents my personal experience and opinions only, and does not in any way, shape, or form represent any employers, past or present.
|Reinforcement learning livestreams
(click links to watch recordings!)
|Hackathon judging, mentoring|