Ye Mao

I am a final-year PhD candidate in Computer Vision and Machine Learning at Imperial College London, supervised by Prof. Krystian Mikolajczyk and supported by the Imperial President's Scholarship . I am currently a research intern at Meta, working on world foundation models for robot learning. My research develops generalizable geometry-aware models for understanding, reconstructing, and generating the 3D physical world. Before my PhD, I completed master's degrees at the University of Cambridge and Imperial, and a bachelor's degree at King's College London, where I first started programming.

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Affiliation Imperial College London
Research 3D Computer Vision, World Model, Physical AI
Selected Research

Publications

* Equal contribution; † Corresponding author.

UniScene3D preview
ECCV 2026

RGB-Pointmap Pretraining for Unified 3D Scene Understanding

Ye Mao, Weixun Luo, Ranran Huang, Junpeng Jing, Krystian Mikolajczyk

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Match Stereo Videos preview
TPAMI 2026

Match Stereo Videos via Bidirectional Alignment

Junpeng Jing, Ye Mao†, Anlan Qiu, and Krystian Mikolajczyk

NAS3R teaser
CVPR 2026

From None to All: Self-Supervised 3D Reconstruction via Novel View Synthesis

Ranran Huang, Weixun Luo, Ye Mao, and Krystian Mikolajczyk

Project Page Paper

Lite Any Stereo overview
CVPR 2026

Lite Any Stereo: Efficient Zero-Shot Stereo Matching

Junpeng Jing, Weixun Luo, Ye Mao†, and Krystian Mikolajczyk

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CVPR Findings 2026

POMA-3D: The Point Map Way to 3D Scene Understanding

Ye Mao, Weixun Luo, Ranran Huang, Junpeng Jing, and Krystian Mikolajczyk

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DYNAMIC teaser
Analytical Chemistry 2026

DYNAMIC: A Novel Software Implementation of a Kinetic Model of TaqMan PCR

Louis Kreitmann, Ye Mao, Ke Xu, Alison Holmes, Karen Brengel-Pesce, Laurent Drazek, and Jesus Rodriguez-Manzano

Paper

Stereo Any Video preview
ICCV Highlight 2025

Stereo Any Video: temporally consistent stereo matching

Junpeng Jing, Weixun Luo, Ye Mao†, and Krystian Mikolajczyk

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Hypo3D preview
ICML 2025

Hypo3D: Exploring Hypothetical Reasoning in 3D

Ye Mao, Weixun Luo, Junpeng Jing, Anlan Qiu, and Krystian Mikolajczyk

Project Page Paper Code BMVA Talk

OpenDlign preview
NeurIPS 2024

OpenDlign: Enhancing Open-World 3D Learning with Depth-Aligned Images

Ye Mao, Junpeng Jing, and Krystian Mikolajczyk

Project Page Paper Code

Match-Stereo-Videos preview
ECCV 2024

Match-Stereo-Videos: Bidirectional Alignment for Consistent Dynamic Stereo Matching

Junpeng Jing, Ye Mao†, and Krystian Mikolajczyk

Project Page Paper Code

DisC-Diff preview
MICCAI 2023

DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution

Ye Mao*, Lan Jiang*, Xi Chen, and Chao Li

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CoLa-Diff preview
MICCAI 2023

CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis

Lan Jiang*, Ye Mao*, Xi Chen, and Chao Li

Project Page Paper Code

Deep domain adaptation for multiplexing preview
IEEE JBHI 2023

Deep Domain Adaptation Enhances Amplification Curve Analysis for Single-Channel Multiplexing in Real-Time PCR

Ye Mao, Ke Xu, Luca Miglietta, Louis Kreitmann, Nicolas Moser, Pantelis Georgiou, Alison Holmes, and Jesus Rodriguez-Manzano

Paper

Academic Record

Experience

Education

  • PhD in Computer Vision and Machine Learning 2023-present
    Imperial College London
  • MPhil in Medical Sciences 2022-2023
    University of Cambridge Thesis: Brain MRI Super-Resolution using Conditional Diffusion Model
  • MSc in Applied Machine Learning 2021-2022
    Imperial College London First Class Honours, top overall grade: 81%; thesis grade: 87% Thesis: Domain Adaptation for Digital PCR Multiplexing
  • BSc in Computer Science 2018-2021
    King's College London First Class Honours, top overall grade: 82%; thesis grade: 81% Thesis: String Sanitisation Algorithm Development

Research Experience

  • Research Assistant 2024-2025
    Centre for Antimicrobial Optimisation Lab, Imperial College London
  • Research Assistant Jan 2023-Sep 2023
    Cambridge Brain Tumour Imaging Lab, University of Cambridge

Teaching

  • Graduate Teaching Assistant 2024-present
    Imperial College London
    • Deep Learning (ELEC60009)
    • Computer Vision and Pattern Recognition (ELEC70073)
  • Undergraduate Teaching Assistant 2021
    King's College London
    • Foundation of Computing
    • Robotics Group Project

Academic Service

  • Computer Vision CVPR (2025-2026), ECCV (2024, 2026), ICCV (2025), TPAMI
  • Machine Learning NeurIPS (2024-2026), ICML (2025-2026), ICLR (2025-2026)
  • Medical Imaging IEEE Transactions on Medical Imaging, MICCAI (2024-2026)

Professional Skills

  • Python, PyTorch, TensorFlow, C++, Java, OpenCV, Git, LaTeX
Recognition

Awards

  • 2023
    Imperial President’s PhD Scholarship Among the top 50 selected college-wide
  • 2023
    The Humanitarian Trust GBP 1,000 funding to support MPhil study in Clinical Neuroscience
  • 2022
    Applied Machine Learning Prize Highest overall grade in MSc Applied Machine Learning
  • 2022
    Hertha Ayrton Centenary Prize Highest final-year project grade in the Imperial EEE department
  • 2021
    Robotics Prize Highest overall grade in BSc Computer Science and Robotics
  • 2021
    Peplow Prize Highest final-year project grade in King's Informatics department