As AI capabilities surpass our own, the defining challenge shifts from pursuing a monolithic
intelligence to designing a truly collaborative partner. My research builds this critical bridge by
drawing wisdom from the very source of human progress: our own collective intelligence. I work not
only to build standalone AI systems that can accomplish human requests, but to learn from human
cooperation to design a new form of collective intelligence at scale—one where AI agents integrate
into our society not just as a powerful tool, but as true partners that can co-create with humans
seamlessly.
At Google DeepMind, my work involves building some of the largest and most capable models today. I was a core contributor to the training of the
Gemini
family of models (1.0, 1.5, and 2.5) and also helped develop the open-source 
Gemma
models.
My passion for collaborative AI began during my PhD, where my research explored steerability, reliability, and complex problems at the intersection of LLMs and RL. My work on reinforced inference-time alignment was honored with a
Best
Paper Award at
AAAI 2021.
You can find all my publications on my Google Scholar.
I'm always open to interesting conversations. Feel free to reach me at my personal email or work email.
At Google DeepMind, my work involves building some of the largest and most capable models today. I was a core contributor to the training of the
Gemini
family of models (1.0, 1.5, and 2.5) and also helped develop the open-source Gemma
models.
My passion for collaborative AI began during my PhD, where my research explored steerability, reliability, and complex problems at the intersection of LLMs and RL. My work on reinforced inference-time alignment was honored with a
Best
Paper Award at
AAAI 2021.
You can find all my publications on my Google Scholar.
I'm always open to interesting conversations. Feel free to reach me at my personal email or work email.