Ye MaoPhD Candidate (President Scholar)Dept. of Electrical and Electronic Engineering Imperial College London London, UK Email: ye.mao21@imperial.ac.uk Github: Link Google Scholar: Link LinkedIn: Link |
|
I am currently a second-year PhD candidate specializing in Computer Vision and Machine Learning at MatchLab, Imperial College London. My research is supervised by supported by Prof. Krystian Mikolajczyk and funded by the Imperial President's Scholarship. Research Interest: 3D Scene Understanding, Vision-Language Model, and Open-Vocabularly Learning.
Prior to my PhD journey, I completed an MPhil in Medical Sciences at the University of Cambridge and an MSc in Applied Machine Learning at Imperial College London. My undergraduate studies were in Computer Science at King's College London.OpenDlign: Enhancing Open-World 3D Learning with Depth-Aligned Images Ye Mao, Junpeng Jing, and Krystian Mikolajczyk NeurIPS 2024. [Project Page] [NeurIPS] [Code] |
|
Match-Stereo-Videos: Bidirectional Alignment for Consistent Dynamic Stereo Matching Junpeng Jing, Ye Mao, and Krystian Mikolajczyk ECCV 2024. [Project Page] [ECCV] [Code] |
|
DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution Ye Mao, Lan Jiang, Xi Chen, and Chao Li MICCAI 2023. [Project Page] [MICCAI] [Code] |
|
CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis Lan Jiang, Ye Mao, Xi Chen, and Chao Li MICCAI 2023. [Project Page] [MICCAI] [Code] |
|
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 IEEE Journal of Biomedical and Health Informatics. [IEEE JBHI] |