Wang Xiaoye

Wang Xiaoye

MPhil student at Cambridge & Graduate Research Fellow at INSAIT

I work on computer vision and machine learning, with current interests in 3D perception, generative modeling, and vision for healthcare.

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About Me

I am a Graduate Research Fellow and Visiting Researcher at INSAIT, where I work with Prof. Luc Van Gool and Dr. Danda Paudel on 3D vision.

I recently completed my MPhil in Data Intensive Science at the University of Cambridge. During that period, I also interned at MMLAB@CUHK with Prof. Xiangyu Yue and Dr. Wei-Hong Li.

Before that, I received my BSc in Mathematics from Harbin Institute of Technology in 2024. In my final undergraduate year, I received the Singapore International Pre-Graduate Award (SIPGA) and worked at I2R, A*STAR with Dr. Jun Cheng and at NUS with Prof. Dianbo Liu.

My research interests are in computer vision and machine learning, especially 3D vision, generative models, and healthcare-related applications.

Research Interests

  • 3D vision and geometry-aware learning
  • 2D & 3D Generative models
  • Computer vision for healthcare applications

News

  • [2026.02] Paper accepted to CVPR 2026

    My first first-author paper on 3D-aware multi-task learning has been accepted to CVPR 2026!

  • [2025.09] Joined INSAIT as a Graduate Research Fellow

    I joined INSAIT as a Graduate Research Fellow, where I work on 3D vision and generative modeling to build digital twins for real-world objects and environments.

  • [2025.08] Completed my MPhil in Data Intensive Science at Cambridge

    I completed my MPhil in Data Intensive Science at the University of Cambridge, where I focused on data-intensive machine learning. My thesis, Transforming Drug Discovery with Generative AI and Foundation Models, explored the use of generative AI and foundation models for medical image translation and drug discovery.

  • [2024.06] Graduated from Harbin Institute of Technology

    I graduated from HIT with a Bachelor’s degree in Information and Computing Science and was honored to be recognized as both a Provincial Outstanding Graduate (top 6% in the province) and a University Outstanding Graduate.

  • [2023.12] Paper accepted to AAAI 2024

    My work on retinal image registration, conducted during my internship at I2R, A*STAR, was accepted to AAAI 2024!

Selected Publications

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