I am Sharon, a CS PhD student and Knight-Hennessy scholar at Stanford University advised by Ron Fedkiw and Chris Manning. I earned my Master’s from Stanford, where I worked with Jiajun Wu and Fei-Fei Li at the Stanford Vision and Learning Lab, and my Bachelor’s in EECS with Honors from UC Berkeley.
My research interest lies in vision foundation models and graphics. In particular, I work on controllable 2D and 3D generation.
Recently, I worked on BEHAVIOR and co-led NOIR, a brain-robot interface for long-horizon tasks.
Email: sharonal (at) stanford.edu
News
🔊 Nov 2024: Featured in TheStar newspaper
🔊 May 2024: Recieved my M.S. in Computer Science at Stanford University
🔊 Oct 2023: Received the Siebel Scholar Award
Outside academia, I founded a nonprofit to help orphans access basic needs and education. I’ve also represented California students at the Capitol, discussing with congressmen for educational and social policies.
Research
BEHAVIOR Vision Suite: Customizable Dataset Generation via Simulation
Yunhao Ge*, Yihe Tang*, Jiashu Xu*, Cem Gokmen*, Chengshu Li, Wensi Ai, Benjamin Jose Martinez, Arman Aydin, Mona Anvari, Ayush K Chakravarthy, Hong-Xing Yu, Josiah Wong, Sanjana Srivastava,
Sharon Lee,
Shengxin Zha, Laurent Itti, Yunzhu Li, Roberto Martín-Martín, Miao Liu, Pengchuan Zhang, Ruohan Zhang, Li Fei-Fei, Jiajun Wu
Conference on Computer Vision and Pattern Recognition (CVPR), 2024
Highlight project page
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arXiv
NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities
Ruohan Zhang*,
Sharon Lee*,
Minjune Hwang*, Ayano Hiranaka*, Chen Wang, Wensi Ai, Jin Jie Ryan Tan, Shreya Gupta, Yilun Hao, Gabrael Levine, Ruohan Gao, Anthony Norcia, Li Fei-Fei, Jiajun Wu
Conference on Robot Learning (CoRL) , 2023
Oral Presentation at Bridging the Gap between Cognitive Science and Robot Learning Workshop at CoRL 2023
project page
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arXiv