About Me

I am a Staff Research Engineer at Google DeepMind in New York City, where I develop AI systems that learn from multimodal, real-world data. My research brings together audio, vision, language, and structured signals to advance how machines perceive, reason about, and generate human-centered content.

At Google DeepMind, I contribute to the Gemini family of models, with a focus on multimodal understanding and expressive interaction. My work spans foundational model research, generative systems, and translating emerging capabilities into real-world applications. Across these efforts, I am driven by the goal of building AI that is technically robust, perceptive, and useful to society.

Previously, I was with Google Research. I earned my PhD in Electrical and Computer Engineering from the University of Southern California, where I was advised by Prof. Shri Narayanan at the Signal Analysis and Interpretation Laboratory. My academic background is rooted in multimodal representation learning and affective computing. I earned my Master’s degree in Electrical Engineering from UC Santa Barbara and worked as a Junior Research Scientist at NYU Langone Medical Center, developing statistical models of functional brain networks using fMRI.

Outside of research, I write stories, and sometimes use the tools I build to bring them to life: Between the Lines.

Research Areas