I am a Staff Researcher at Airbnb, where I lead reinforcement learning research for search and personalization systems at scale.

Prior to Airbnb, I was a technical lead at Netflix, where I spearheaded the development of the contrastive learning framework that underpins several core personalization algorithms across the Netflix homepage and mobile experience.

Before that, at Apple, I developed language models for query and intent understanding. I co-authored a patent for my work in language understanding. I also developed human-in-the-loop systems for continuous learning, advancing Apple Search’s query understanding capabilities.

I received my Ph.D. in Machine Learning from Carnegie Mellon University, where I was advised by the late Jaime Carbonell. My dissertation focused on active learning and transfer learning, contributing foundational work to adaptive data-efficient modeling.

I am an entrepreneur at heart: I co-founded two AI startups, translating research breakthroughs into practical systems deployed in production environments.

I was awarded the Apple Women in Technology Award and Carnegie Mellon’s Richard King Mellon Fellowship. My work has been featured in several media outlets, including TechCrunch and The Verge.

My research interests span sequential modeling, personalization, and reinforcement learning, focusing on real-world deployment and human-centered AI systems.