Recipient of the Ben Wegbreit Prize for best thesis in Computer Science at Stanford
Awarded Stanford’s Firestone Medal for excellence in research
Published multiple papers at top-tier venues including NeurIPS, ICLR, CVPR, ICML, and CoRL
Best Poster Award at NeurIPS ICBINB Workshop 2023
Notable works include 'From Programs to Poses', 'Neuro-Symbolic Decoding of Compositional Structure in Human fMRI', 'What Makes a Maze Look Like a Maze?', and 'NS3D: Neuro-Symbolic Grounding of 3D Objects and Relations'
Background
Ph.D. candidate in Computer Science and Knight-Hennessy Scholar at Stanford University
Research focuses on artificial intelligence and computer vision
Advised by Prof. Jiajun Wu in the CogAI group & Stanford Vision and Learning Lab (SVL)
Research interests lie in visual reasoning and neuro-symbolic learning
Aims to build generalist models that leverage decomposition, abstraction, and structural priors to interpret the world like humans and solve complex tasks in data-scarce domains