Daniel graduated from the Massachusetts Institute of Technology with a Bachelor's Degree in Computer Science and Engineering in 2022 and a Masters of Engineering in Electrical Engineering and Computer Science in 2023. He began his PhD in Computer Science in Fall of 2023, and joined NRG in Spring 2026. His research lies at the intersection of robotics, computer vision, and representation learning, with a focus on robot learning for physically grounded and structured perception. He aims to build models that capture the underlying structure of the physical world, enabling generalizable perception, planning, and control in embodied agents.
