Machine Learning Engineer
I architect and ship production AI systems — from conversational avatars and document understanding at Amira Learning, to causal inference and RAG pipelines at Causely, to Siri observability at Apple. I hold an MS in CS from NYU Courant, a published record in fair ML, and a US patent in AI-driven systems assurance. I write about AI, LLMs, and the science of learning.
Conversational AI avatars, document understanding pipelines, and reading assessment systems powering K-12 education at scale.
Causal inference engine, anomaly detection, and RAG-based DevOps tooling for automated root-cause analysis.
Siri Observability team — built ML monitoring and analysis tools for one of the world's largest voice assistants.
Research in model fairness and medical AI. TA for Machine Learning, NLP, and Data Science.
Automatic bias detection in facial analysis models — published at IEEE/CVF WACV.
CNN-based chest X-ray analysis to assist radiologists in differentiating COVID-positive patients. Published in European Radiology.
A fast, native desktop client for X (Twitter) built with Electron and TypeScript.