About Me
As a final year Ph.D. student in the Department of Computer Science at the University of Hong Kong, I am conducting research under the supervision of Prof. Ping Luo and Prof. Wenping Wang (opens new window). My academic journey began with a foundation in EE from Shenzhen University, under the guidance of Prof. Lin Di.
My research interests are currently centered in the field of AI, with a special focus on its application in medicine, with the goal of developing systems that are not only powerful, but also trustworthy.
Inspired by pioneers in the field, my work seeks to contribute to the potential of AI to improve healthcare diagnostics and treatment strategies. The goal is to advance the intersection of technology and healthcare, enabling improved patient outcomes through the application of AI.
Please feel free to contact us via email at u3008013@connect.hku.hk.
News
- [2024-01] AutoBench is accepted by ICLR24. See you in Wien
- [2023-11] I joint the Prof. Ruijiang Li (opens new window)'s group at Stanford University as a visiting student.
- [2023-07] DDP is accepted by ICCV23. See you in Paris
- [2022-11] DrugOOD is accepted by AAAI23.
- [2022-10] AMOS is accepted by NIPS22. See you in New Orleans
Publications
→ Full list (opens new window)
Large Language Models as Automated Aligners for benchmarking Vision-Language Models
Yuanfeng Ji*, Chongjian Ge*, Weikai Kong, Enze Xie, Zhengying Liu, Zhengguo Li, Ping Luo
ICLR 2024
Introduction: This research explores the potential of large language models as automated aligners, setting a new benchmark in vision-language model evaluation.
[Paper (opens new window)] [Code&Data(wip) (opens new window)]
SyNDock: N Rigid Protein Docking via Learnable Transformation Synchronization
Yuanfeng Ji, Yatao Bian, Guoji Fu, Peilin Zhao, Ping Luo
Tech report
Introduction: SyNDock presents an innovative approach to protein docking, utilizing learnable transformation synchronization for enhanced accuracy and efficiency.
DDP: Diffusion Model for Dense Visual Prediction
Yuanfeng Ji*, Zhe Chen*, Enze Xie, Lanqing Hong, Xihui Liu, Zhaoqiang Liu, Tong Lu, Zhenguo Li, Ping Luo
ICCV 2023
Introduction: A groundbreaking approach to dense visual prediction, employing diffusion models to enhance accuracy and efficiency.
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery
Yuanfeng Ji*, Lu Zhang*, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian
AAAI 2023 (Oral)
Introduction: DrugOOD serves as a curator and benchmark for AI-driven drug discovery, focusing on affinity prediction problems with noise annotations.
[Paper (opens new window)] [Code (opens new window)] [Project (opens new window)]
AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation
Yuanfeng Ji, Haotian Bai, Chongjian Ge, Jie Yang, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, Ping Luo
Neuips 2022 (Oral)
Introduction: AMOS stands as a large-scale benchmark for abdominal multi-organ segmentation, paving the way for advancements in medical image analysis.
[Paper (opens new window)] [Code (opens new window)] [Challenge (opens new window)]
Multi-compound Transformer for Accurate Biomedical Image Segmentation
Yuanfeng Ji, Ruimao Zhang, Huijie Wang, Zhen Li, Lingyun Wu, Shaoting Zhang, Ping Luo
MICCAI 2021 (Early Accept)
Introduction: This work introduces a transformative approach in biomedical image segmentation, leveraging a multi-compound transformer architecture for enhanced accuracy.
UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation
Yuanfeng Ji, Ruimao Zhang, Zhen Li, Jiamin Ren, Shaoting Zhang, Ping Luo
MICCAI 2021 (Early Accept)
Introduction: UXNet propels the search for multi-level feature aggregation in 3D medical image segmentation through an AutoML tool for network design.
[Paper (opens new window)] [[Code(coming)]]
PRSNet: Part Relation and Selection Network For Bone Age Assessment
Yuanfeng Ji, Hao Chen, Dan Lin, Xiaohua Wu, Di Lin
MICCAI 2020 (Early Accept)
Introduction: PRSNet innovates bone age assessment by integrating part relation and selection networks to streamline the analysis process.
RANet: Region Attention Network for Semantic Segmentation
Dingguo Shen*, Yuanfeng Ji*, Ping Li, Yi Wang, Di Lin
Neuips 2020
Introduction: RANet leverages region-based attention mechanisms to enhance the performance of semantic segmentation tasks.
Multi-Scale Context Interwining for Semantic Segmentation
Di Lin, Yuanfeng Ji, Dani Lischinski, Daniel Cohen-Or, Hui Huang
ECCV 2018
Introduction: MSCI introduces an innovative approach to semantic segmentation by intertwining multi-scale contextual information, enhancing the accuracy and robustness of the segmentation process.
Challenges & Achievements
- [2019] Ranked 5th in the Kaggle RSNA Pneumonia Detection Challenge (opens new window) (Gold Medal).
- [2019] Ranked 3rd in the COCO 2019 Panoptic Segmentation Task (opens new window).
- [2018] Ranked 3rd in the MICCAI 2018 ISIC Skin Lesion Segmentation Challenge (opens new window).
- [2019] Ranked 87th in the Kaggle Human Protein Atlas Image Classification Challenge (opens new window) (Silver Medal).
Professional Activities
- Organizer for the Multi-Modality Abdominal Multi-Organ Segmentation Challenge (opens new window) at MICCAI 2022.
- Journal Reviewer for TMI, TMM.
- Conference Reviewer for CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, MICCAI.
Experience
I am deeply grateful for the growth and learning I have experienced under the guidance of my respected mentors.
- [2023-11 ~ Present] Visiting Student at Stanford University, advised by Prof.Ruijiang Li (opens new window)
- [2023-04 ~ 2023-11] Research Intern at Huawei Noah's Ark Lab, advised by Dr.Enze Xie (opens new window)
- [2021-04 ~ 2023-04] Research Intern at Tencent AI Lab, advised by Dr.Yatao Bian (opens new window)
- [2019-07 ~ 2020-10] Research Intern at SenseTime Research, advised by Prof.Ruimao Zhang (opens new window)
- [2018-05 ~ 2019-06] Research Intern at Imsight Medical Technology, advised by Prof.Hao Chen (opens new window)