About

I’m an ML architect at PayPal, 12 years. ~1,500 services across cloud, data, and developer productivity — demand forecasting, autoscaling, anomaly detection, model governance.

I came up through research: crowdsourcing and planetary robotics in grad school (NSF, NASA NIAC funded), then cryptographic systems with Doug Crockford, then building PayPal’s enterprise ML platform and shipping applied ML. 6 peer-reviewed papers, 337 citations. AAAI HCOMP Test of Time Award.

I write about what actually works (and what doesn’t) when you apply ML to real infrastructure at scale. This blog focuses on demand forecasting, reinforcement learning for autoscaling, and the engineering between a model and production.

Find me on LinkedIn or Google Scholar.