Kexue Fu is an associate professor at Shandong Computer Science Center (National Supercomputer Center in Jinan) 
in Qilu University of Technology (Shandong Academy of Sciences). He is now working on Embodied AI, 3DV and Medical LMs. If you are seeking any form of academic cooperation, please feel free to email kexue at kexue.work@gmail.com. He is hiring interns!
Kexue received his Ph.D. (2018-2023) from Fudan University / Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention, advised by Prof. Manning Wang. He is fortunate to have internships at Shanghai AILab 
.
His research interest includes Embodied AI, Machine Vision, and Medical Large Models. He has published 30+ papers 
His works include RGM, FAST, POS-BERT, and PointMBF.
🔥 News
- [2024-09] 🎉 1 paper accepted to NeurIPS 2024.
- [2024-06] 🎉 1 paper accepted to CVPR 2024.
- [2023-12] 🎉 1 paper accepted to AAAI 2024.
- [2023-11] 🎉 1 paper accepted to Bioinformatics.
- [2023-11] 🎉 1 paper accepted to Elsevier ESWA.
- [2023-10] 🎉 1 paper accepted to ACM MM 2023.
- [2023-07] 🎉 1 paper accepted to ICCV 2023.
- [2023-06] 🎉 1 paper accepted to IEEE TCSVT.
📝 Publications
Machine Vision
Robust Point Cloud Registration Framework Based on Deep Graph Matching
Kexue Fu, Shaolei Liu, Xiaoyuan Luo, Manning Wang
- Propose a novel deep graph matching based framework for point cloud registration.
- Propose a module based on deep graph matching to calculate graph edge.
PointMBF: A Multi-scale Bidirectional Fusion Network for Unsupervised RGB-D Point Cloud Registration
Mingzhi Yuan, Kexue Fu, Zhihao Li, Yucong Meng, Manning Wang
- Propose a network implementing multi-scale bidirectional fusion strategy.
- Our method achieves new state-of-the-art performance on ScanNet and 3DMatch.
PI-NeRF: A Partial-Invertible Neural Radiance Fields for Pose Estimation
Zhihao Li, Kexue Fu, Haoran Wang, Manning Wang
- Pose Estimation Without Initialization and Iterative Optimization.
- Significant Speed Improvement with Competitive Accuracy.
Zhiwei Yang, Kexue Fu, Minghong Duan, Linhao Qu, Shuo Wang, Zhijian Song
- Novel ‘Separate and Conquer’ Scheme for Co-occurrence Problem.
- Enhanced Semantic Representation with Multi-Granularity Knowledge Contrast.
🏥 Medical LMs
FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification
Kexue Fu, Xiaoyuan Luo, Linhao Qu, Shuo Wang, Ying Xiong, Ilias Maglogiannis, Longxiang Gaom, Manning Wang
- A novel and efficient dual-tier few-shot learning paradigm for WSI classification.
- Approache the accuracy of fully supervised methods with only 0.22% annotation costs.
Linhao Qu, Xiaoyuan Luo, Kexue Fu, Manning Wang, Zhijian Song
- Few-Shot Weakly Supervised Learning for WSI Classification
- Two-Level Prompt Learning with Vision-Language Models.
💊 AI4Science
ProteinMAE: Masked Autoencoder for Protein Surface Self-supervised Learning
Mingzhi Yuan, Ao Shen, Kexue Fu, Jiaming Guan, Yingfan Ma, Qin Qiao, Manning Wang
- A Self-Supervised Framework for Protein Surface Representation.
- Efficiency and Competitive Performance.
🎖 Honors and Awards
- 2023.06, Outstanding Graduate of Shanghai
- 2023.03, Certificate of The Oceanwide Scholar (Top 0.1%)
- 2021.12, National Scholarship (Top 1%)
📖 Educations
- 2018.09 - 2023.06, PhD, MICCAI, Fudan Univeristy, Shanghai.
- 2014.09 - 2018.06, Undergraduate, Wuhan University of Technology, Wuhan.
💬 Invited Talks
- 2023.12, MICS Online Forum | [Video]
- 2023.11, CCF Digital Medicine Symposium, Young Scholars Forum | [Report]
💻 Internships
- 2020.07 - 2021.03, Shanghai AILab, Shanghai.