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Yichao Zhou

Member of Technical Staff at Cartesia

Cartesia.ai

Biography

I am a Member of Technical Staff (MTS) at Cartesia, where I build voice agents. Previously, I was a research scientist in Vladlen Koltun‘s org at Apple, working on video world models and 3D perception, and at Apple’s SLAM team for ARKit.

I earned my Ph.D. degree in Computer Science at UC Berkeley. Prior to Berkeley, I received my Bachelor’s degree from Yao Class at Tsinghua University. Earlier, I received a silver medal at the International Olympiad in Informatics (IOI 2011).

My expertise spans voice AI, video/image synthesis, 3D perception, and neural rendering, with a broader interest in artificial intelligence and computer vision. My PhD research focused on geometric deep learning from images with dissertation on “Learning to Detect Geometric Structures from Images for 3D Parsing”.

Interests

  • Voice Agents
  • Multimodal AI
  • Computer Vision

Education

  • Ph.D. in Computer Science, 2020

    University of California, Berkeley

  • B.Eng in Computer Science and Technology, 2015

    Tsinghua University

Publications

”*” indicates equal contribution

Aleksei Bochkovskii, Amael Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, Stephan R. Richter, Vladlen Koltun (2025). Depth Pro: Sharp Monocular Metric Depth in Less Than a Second. International Conference on Learning Representations (ICLR) 2025.

Preprint

Stergios Roumeliotis, Yichao Zhou, Abdelhamid Dine, Oleg Naroditsky (2024). Pose Predictor for Moving Platform. Patent US20250110567A1, 2024.

Shichen Liu, Yunxuan Cai, Haiwei Chen, Yichao Zhou, Yajie Zhao (2022). Rapid Face Asset Acquisition with Recurrent Feature Alignment. SIGGRAPH Asia 2022.

PDF

Shichen Liu, Yichao Zhou, Yajie Zhao (2021). VaPiD: A Rapid Vanishing Point Detector via Learned Optimizers. CVPR 2021.

PDF

Yichao Zhou, Shichen Liu, Yi Ma (2021). NeRD: Neural 3D Reflection Symmetry Detector. CVPR 2021.

Preprint Code

Yichao Zhou (2020). Learning to Detect Geometric Structures from Images for 3D Parsing. Doctoral Dissertation.

PDF Video

Yichao Zhou, Jingwei Huang, Xili Dai, Linjie Luo, Zhili Chen, Yi Ma (2020). HoliCity: A City-Scale Data Platform for Learning Holistic 3D Structures. Technical Report. arXiv:2008.03286 [cs.CV].

Preprint Code Project

Yichao Zhou, Shichen Liu, Yi Ma (2020). Learning to Detect 3D Reflection Symmetry for Single-View Reconstruction. Technical Report. arXiv:2006.10042 [cs.CV].

Preprint Code

Jingwei Huang, Yichao Zhou, Leonidas Guibas (2020). ManifoldPlus: A Robust and Scalable Watertight Manifold Surface Generation Method for Triangle Soups. Technical Report. arXiv:2005.11621 [cs.GR].

Preprint Code

Yichao Zhou, Haozhi Qi, Jingwei Huang, Yi Ma (2019). NeurVPS: Neural Vanishing Point Scanning via Conic Convolution. NeurIPS 2019.

Preprint Code Poster Slides

Yichao Zhou, Haozhi Qi, Yi Ma (2019). End-to-End Wireframe Parsing. ICCV 2019.

Preprint Code Poster

Jingwei Huang, Yichao Zhou, Thomas Funkhouser, Leonidas Guibas (2019). FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image. ICCV 2019.

Preprint Code

Yichao Zhou, Haozhi Qi, Simon Zhai, Qi Sun, Zhili Chen, Li-Yi Wei, Yi Ma (2018). Learning to Reconstruct 3D Manhattan Wireframes from a Single Image. ICCV 2019 (Oral Presentation).

Preprint Code Dataset Poster Video

Jingwei Huang*, Yichao Zhou*, Matthias Nießner, Jonathan Shewchuk, Leonidas Guibas (2018). QuadriFlow: A Scalable and Robust Method for Quadrangulation. SGP 2018 (Best Paper), Computer Graphics Forum.

PDF Code Dataset Demo Online Tool

Yichao Zhou, Wei Chu, Sam Young, Xin Chen (2017). BandNet: A Neural Network-Based, Multi-Instrument Beatles-Style MIDI Music Composition Machine. ISMIR 2019.

Preprint Poster Slides Audio

Yichao Zhou, Bruce R. Donald, Jianyang Zeng (2016). Parallel Computational Protein Design. Methods in Molecular Biology.

PDF Code

Yichao Zhou, Yuexin Wu, Jianyang Zeng (2015). Computational Protein Design Using AND/OR Branch-and-Bound Search. RECOMB 2015.

Preprint Code Dataset Slides

Yichao Zhou, Jianyang Zeng (2015). Massively Parallel A* Search on a GPU. AAAI 2015 (Oral Presentation).

PDF Code Slides Appendix

Yichao Zhou, Wei Xu, Bruce R. Donald, Jianyang Zeng (2014). An Efficient Parallel Algorithm for Accelerating Computational Protein Design. ISMB 2014, Bioinformatics.

PDF Code Dataset Poster Slides

Awards

Press Coverage

New Scientist Magazine, Issue 3214
Archive.org

Blog Posts

Yet Another Tutorial on Diffusion Models
I will explain diffusion models from DDPM and DDIM, then connect them to EDM, score-based generative modeling, and rectified flow.
Apr 28, 2026 7 min read math
Yet Another Tutorial on PPO
I will explain PPO from its surrogate objective, its relationship to policy gradient, importance-ratio clipping, GAE, and critic/value-network training.
Apr 26, 2026 8 min read math
How to Downgrade the MacOS System (2025 Version)
A guide to downgrading from macOS beta to a stable version on Apple Silicon Macs, including backup tips and Migration Assistant workarounds.
May 28, 2025 2 min read IT
Uniform Sampling on Disks, Shells, Balls, and Triangles.
I will discuss the generalized approach to sample points on an arbitrary geometry.
Mar 10, 2024 3 min read math
Orientation Estimation from IMUs with Error-State Kalman Filters
I will discuss the math and intuition behind the 3D altitude filter, linear Kalman filter, extended Kalman filter, error-state Kalman filter, and Lie group calculus for deriving the math for orientation estimation.
Oct 23, 2022 17 min read math
See all posts

Experience

 
 
 
 
 
August 2026 – Present

Member of Technical Staff

Cartesia.ai

I build voice agents.
 
 
 
 
 
February 2021 – June 2026
California, USA

Research Scientist

Apple Inc.

I was a research scientist in Vladlen Koltun‘s Photorealism team at Apple, working on video world models. Previously, I worked at the Apple SLAM team for ARKit on Vision Pro.
 
 
 
 
 
May 2019 – August 2019
3000 El Camino Real, Palo Alto, CA 94306

Research Intern

Bytedance Inc.

I created a real-world data platform of urban environments by aligning the city CAD model to the street-view panorama images. I was advised by Yi Ma and Linjie Luo.
 
 
 
 
 
May 2018 – August 2018
345 Park Ave, San Jose, CA 95110

Research Intern

Adobe Research

I did the research on how to reconstruct a 3D scene for urban environments by utilizing their global regularities and symmetries. I enjoyed my time with my advisors Qi Sun, Zhili Chen, Li-Yi Wei, and Kalyan Sunkavalli.
 
 
 
 
 
May 2017 – August 2017
523 Ocean Front Walk, Venice, CA 90291

Research Intern

Snapchat Inc.

I worked on a project about algorithm-based Beatles-style music composition with the help from an outstanding composer and percussionist Sam Young at UCLA. I was advised by Wei Chu and Xin Chen.
 
 
 
 
 
May 2016 – August 2016
1901 S Bascom Ave #1300, Campbell, CA 95008

Research Intern

Bellus 3D Inc.

During the internship, I implemented a software to deform a face mesh to fit the point cloud of a scanned face along with the Morphable Face Model. I was advised by James Davis and Jing Liu.
 
 
 
 
 
September 2015 – December 2020
University of California, Berkeley, CA 94720

Research Assistant

University of California, Berkeley

I received my Ph.D. degree here. My advisor is Prof. Yi Ma. My dissertation is on “Learning to Detect Geometric Structures from Images for 3D Parsing”.
 
 
 
 
 
December 2013 – June 2015
30 Shuangqing Rd, Haidian District, Beijing 100084

Research Assistant

Tsinghua University

Advised by Jianyang Zeng, I did research related to the proteins’ 3D structures in the Machine Learning and Computational Biology Group at IIIS when I was an undergraduate. I designed fast and massively parallel combinotorial search algorithms and tested them on the protein design problems. I also implemented a CUDA version of RELION to accelerate the 3D reconstruction of protein structures from cryo-microscopy images, which later turned into my undergraduate thesis.
 
 
 
 
 
August 2013 – November 2013
5 Danling St, Haidian District, Beijing 100080

Research Intern

Microsoft Research Asia

I was a research intern in the Natural Language Processing Group at MSRA, advised by Jianwen Zhang. I studied method of applying Markov Logic Network for the knowledge database completion problem to fill in the missing entires in Freebase.

Service

I was a teaching assistant of the following courses at UC Berkeley:

Skills

Python

Deep Learning

C++

CUDA

Blender 3D

OpenGL/GLSL