Shreya Shankar is a PhD candidate at UC Berkeley's EPIC Lab building AI-powered data systems that are reliable and cost-efficient. A Stanford-trained engineer who worked at Google Brain and Meta, she bridges academic research and industry practice through DocETL (an open-source LLM data processing system with 3.5K+ GitHub stars used by 30+ S&P 500 companies), an O'Reilly book on AI evals co-authored with Hamel Husain, and a Maven course that has reached 4,500+ professionals. She is on the CS faculty job market and gave a faculty candidate talk at Carnegie Mellon in March 2026.
ZeroEval is a New York-based AI startup from Y Combinator's Summer 2025 batch building an auto-optimizer for AI agents. Founded by Jonathan Chavez and Sebastian Crossa - two friends who met in college in Mexico - the platform captures every interaction your AI agent makes, scores quality with custom LLM judges, and automatically turns real production data into better prompts. The result: agents that get smarter after launch without manual intervention. Trusted by DoorDash, Datadog, Hugging Face, and Harvard Medical School, ZeroEval closes what the founders call 'the last mile reliability gap' in agentic AI.