John Mark Agosta works as an applied researcher, with 30 years of experience with numerous startups and labs in the Bay Area. Most recently he was at Microsoft where he worked as a data scientist with cloud customers building models for applications in supply chain, pricing, root cause analysis, compute cluster autoscaling, network anomaly detection, and electronic health record simulation.

A varied career before joining Microsoft gave him broad industry experience working in machine learning and AI at the interface between industry and academia. He received his Ph.D. in Stanford's Management Science and Engineering Department. His background at SRI International, Toyota, Intel Research, and a handful of startups extends back to the early days of AI. His dedication to the field is shown by his participation over the years in first-tier academic machine learning conferences, including co-founding the Bayesian Applications Workshop at for the Uncertainty in AI Conference. Over time he has written over 30 peer-reviewed publications and has 6 accepted patents.