Research

My interests are in scalable training objectives and adaptive inference methods for large-scale generative models. My work bridges foundational machine learning with strong empirical performance to scale inference, enhance capabilities, and improve the efficiency of multimodal agents across language, vision, and time-series data.

^* Equal contribution

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