I optimize for impact. I strive to work with talented people to do amazing things. If you are a misfit, a rebel, or a troublemaker working on something interesting, feel free to send me a message.
I’m an engineer, researcher, and educator that has helped start teams at innovative organizations such as Amazon Alexa and RideOS.
I run a consultancy helping companies across verticals deliver machine learning and data-driven solutions to their hardest problems with a special focus on NLP, recommendation systems, tabular data, and computer vision domains. We’ve helped teams deliver 33% lift on key business metrics in <6 weeks. If that is of interest, don’t hesitate to reach out.
- I’ve been published at the top artificial intelligence conferences in the world. My work has also gotten news coverage. Check out my past projects for a full list of publications.
- I spent several years in the Stanford Natural Language Processing Group, where I had the great fortune to work with Christopher Manning, Percy Liang, and Christopher Potts.
- I think and write about trends in AI research. People have found my past writeups helpful.
- I was the 8th hire at RideOS a Sequoia VC-backed autonomous mobility startup acquired by Gopuff.
- I’m problem-driven (not tool-driven) so I build across the full engineering stack from hardware to software.
- I like to hack for fun. Here are some side projects I’ve worked on.
- I have studied at the top institutions in the world.
- I believe in paying things forward, so I build tools and create resources to help people learn. Check out my blog to see what I teach about.
- We Don’t Need Data Scientists, We Need Data Engineers (>180K Views, Top of Hacker News Front Page, Top KDNuggets Article of 2021)
- A Machine Learning Primer (>50K Views, Top All-Time Reddit r/datascience)
- MLOps Is a Mess But That’s to be Expected (>35K Views, Top of Hacker News Front Page)
- Setting Up a Machine Learning Project (>28K Views) with accompanying starter template
- Complete Artificial Intelligence Undergraduate Course Plan (>22K Views)
- I got into writing answers on Quora a few years back and amassed ~450K views on my answers from a 2 week stretch on the platform.
- What is the Data Science Life Cycle?
- Building a V1 Machine Learning Model
- Machine Learning Error Analysis
I’m a regular co-host on the MLOps Community podcast, where we bring in ML and data industry leaders to get spicy takes on tooling and future trends. The MLOps community is the largest group of MLOps practitioners globally. A sample of some of our shows:
- Model Monitoring in Practice: Krishnaram Kenthapadi - A discussion with the Chief Scientist of Fiddler AI, a leading model monitoring company
- Real-time Data Processing: Jacob Tsafatinos - A discussion with the lead architect of Uber’s ad events processing system
- Making MLFlow: Corey Zumar - A discussion with one of the maintainers of MLFlow, a leading OSS MLOps library from Databricks
- Everything Kubeflow: Ryan Russon - A discussion with a Kubeflow expert on when and why to use this orchestration platform
- Turning Redis into a Composable, ML Data Platform: Sam Partee - A discussion with a Redis Principal AI Engineer on how everyone’s favorite cache is evolving into new ML use-cases
- Building Better Data Teams: Leanne Fitzpatrick - A discussion with the Director of Data Science at the Financial Times on how to organize and manage effective data teams
- Delivering Machine Learning Value: A Guide For Humans - Discord Distinguished Speaker Series
- Interview on ML Career, Education, and More [Apple Podcasts, Google Podcasts, Spotify] - Infinite Machine Learning
- What Researchers and Engineers Can Learn From Each Other - DataTalks.Club
- Pursuing a Career in Artificial Intelligence: Or How I Learned to Stop Worrying and Love the Data - Georgia Tech Data Science Club
- State-of-the-Art is Just the Start: Data Science From Ideation to Deployment - University of Wisconsin Madison Data Science Club
- Key-Value Retrieval Networks For Task-Oriented Dialogue - SIGDial 2017