David Yan

I am an incoming PhD student in Computer Science at Princeton University, advised by Jia Deng. My research is graciously supported by the Francis Robbins Upton Fellowship. Previously, I received my B.S.E. in Computer Science from Princeton.

Recently, I have been interested in understanding what makes good data in computer vision and robotics, especially by leveraging synthetic data.

Email / GitHub / Google Scholar / CV / LinkedIn

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News!

→ I'll be a research intern at Elorian this summer!

→ I received an Honorable Mention for the CRA Outstanding Undergraduate Researcher Award!

→ Slides for my recent work on understanding procedural data generation for stereo depth.

Research

	ProcFunc: Function-Oriented Abstractions for Procedural 3D Generation in Python Alexander Raistrick, Karhan Kayan, Jack Nugent, David Yan, Lingjie Mei, Meenal Parakh, Hongyu Wen, Dylan Li, Yiming Zuo, Erich Liang, Jia Deng arXiv paper / code /
	What Makes Good Synthetic Training Data for Zero-Shot Stereo Matching? David Yan, Alexander Raistrick, Jia Deng CVPR 2026 (Highlight) paper / code /
	Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation Alexander Raistrick, Lingjie Mei, Karhan Kaan Kayan, David Yan, Yiming Zuo, Beining Han, Hongyu Wen, Meenal Parakh, Stamatis Alexandropoulos, Lahav Lipson, Zeyu Ma, Jia Deng CVPR 2024* website / paper / code /
	Infinigen: Infinite Photorealistic Worlds using Procedural Generation Alexander Raistrick, Lahav Lipson, Zeyu Ma* (equal contribution, alphabetical order), Lingjie Mei, Mingzhe Wang, Yiming Zuo, Karhan Kayan, Hongyu Wen, Beining Han, Yihan Wang, Alejandro Newell, Hei Law, Ankit Goyal, Kaiyu Yang, Jia Deng CVPR 2023* website / paper / video / code /