Spring 2025 GRASP SFI: Guandao Yang, Stanford University, “Toward Spatial Intelligence with Limited Data”
January 29 @ 3:00 pm - 4:00 pm
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.
ABSTRACT
Modern artificial intelligences (AIs) rely heavily on internet-scale data with unified representations. However, such large-scale homogeneous data isn’t readily available for spatial computing applications involving 3D geometry, hindering the development of spatial intelligence— AIs that can generate and understand 3D spatial data. In this talk, I will present ideas toward building spatial intelligence systems with limited 3D data. I will discuss my work combining existing mathematical models in graphics with foundation models in machine learning to generate and analyze 3D shapes. Finally, I will conclude with a discussion about the future opportunities and challenges in developing data-efficient AIs for spatial computing and beyond.
Presenter
Guandao Yang
Guandao Yang is a postdoctoral scholar at Stanford, where he works with Professor Leonidas Guibas and Professor Gordon Wetzstein. His research focuses on building AI that can generate and understand shapes. He completed his Ph.D. at Cornell Tech in 2023, where he was advised by Professor Serge Belongie and Professor Bharath Hariharan. During his doctoral studies, Guandao gained experience working at various industry research labs, including NVIDIA, Intel, and Google. He received his bachelor’s degree from Cornell University in Ithaca, majoring in Mathematics and Computer Science.