I am currently a third-year CS Ph.D. student at Johns Hopkins University, advised by Bloomberg Distinguished Professor Alan Yuille.
I received my B.S. in Data Science from Fudan University in 2021. After that, I worked as a research assistant at Shenzhen Research Institute of Big Data, where I was honored to work with Dr. Li Liu and Prof. Chris Ding. I received my M.S.E. in Computer Science from Johns Hopkins University in 2025.
My current research focuses on multi-modal AI agents and foundation models, with applications in medical image analysis, healthcare, and autonomous driving.
I was a Student Researcher at Google Research and a research intern at Waymo. I will return to Google as a research intern in summer 2026.
05/2026, I will join Google as a research intern in summer 2026.
04/2026, 1 survey paper on AI Agents in Healthcare has been accepted by Journal of Biomedical Informatics.
01/2026, 1 paper has been accepted by ISBI 2026 as an oral presentation.
06/2025, 1 paper has been accepted by MICCAI 2025.
05/2025, I join AI Foundation team at Waymo as a research intern.
12/2024, 1 paper has been accepted by NeurIPS 2024.
06/2024, I join Health AI team at Google Research as a student researcher.
12/2023, 1 paper has been accepted by ICASSP 2024.
08/2023, I join CCVL@JHU as a new Ph.D. student.
06/2023, 1 paper has been accepted by MICCAI 2023.
02/2023, 1 paper has been accepted by CVPR 2023.
12/2022, 1 paper has been accepted by ICLR 2023.
12/2022, 1 journal paper has been accepted by IEEE TMI.
Research
I'm interested in building multi-modal AI agents, exploring the mechanism behind large models, and designing efficient training algorithms for multi-modal understanding. I also work on semi-supervised/active/transfer/self-supervised learning and generative modeling, as well as their applications (e.g., medical image analysis and healthcare).
Conference Papers:
Large-Scale Label Quality Assessment for Medical Segmentation via a Vision-Language Judge and Synthetic Data Yixiong Chen, Zongwei Zhou, Wenxuan Li, Alan Yuille
ISBI 2026 | paper | Oral Presentation
CoCa-CXR: Contrastive Captioners Learn Strong Temporal Structures for Chest X-Ray Vision-Language Understanding Yixiong Chen, Shawn Xu, Andrew Sellergren, Yossi Matias, Avinatan Hassidim, Shravya Shetty, Daniel Golden, Alan Yuille, Lin Yang
MICCAI 2025 | paper | Done when interning at Google
MoLE: Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts
Jie Zhu, Yixiong Chen, Mingyu Ding, Ping Luo, Leye Wang, Jingdong Wang
NeurIPS 2024 | paper
Leveraging Noisy Labels of Nearest Neighbors for Label Correction and Sample Selection
Hua Jiang, Yixiong Chen, Li Liu, Xiaoguang Han, Xiaoping Zhang
ICASSP 2024 | paper
MetaLR: Layer-wise Learning Rate based on Meta-learning for Adaptively Fine-tuning Medical Pre-trained Models Yixiong Chen, Jingxian Li, Hua Jiang, Li Liu, Chris Ding
MICCAI 2023 | paper
Which Layer is Learning Faster? A Systematic Exploration of Layer-wise Convergence Rate for Deep Neural Networks Yixiong Chen, Alan Yuille, Zongwei Zhou
ICLR 2023 | paper
HiCo: Hierarchical Contrastive Learning for Ultrasound Video Model Pretraining
Chunhui Zhang, Yixiong Chen, Li Liu, Qiong Liu, Xi Zhou
ACCV 2022 | paper
USCL: pretraining deep ultrasound image diagnosis model through video contrastive representation learning Yixiong Chen, Chunhui Zhang, Li Liu, Cheng Feng, Changfeng Dong, Yongfang Luo, Xiang Wan
MICCAI 2021 | paper | Oral Presentation | Excellent Paper on Artificial Intelligence of Shenzhen
Journal Papers:
A Comprehensive Survey of AI Agents in Healthcare
Guanghao Xu*, Xin Li*, Yixiong Chen*, Yihan Duan*, Shi Wu*, Hanning Yu*, Chak-Hei Chiu, Jianxin Ni, Na Tang, et al.
Journal of Biomedical Informatics 2026 | paper
AbdomenAtlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking
Wenxuan Li, Chongyu Qu, Xiaoxi Chen, Pedro RAS Bassi, Yijia Shi, Yuxiang Lai, Qian Yu, Huimin Xue, Yixiong Chen, Xiaorui Lin, Yutong Tang, Yining Cao, Haoqi Han, Zheyuan Zhang, Jiawei Liu, Tiezheng Zhang, Yujiu Ma, Jincheng Wang, Guang Zhang, Alan Yuille, Zongwei Zhou
Medical Image Analysis 2024 | paper
Generating and weighting semantically consistent sample pairs for ultrasound contrastive learning Yixiong Chen, Chunhui Zhang, Chris HQ Ding, Li Liu
IEEE TMI 2023 | paper | Excellent Paper on Science and Technology of Shenzhen
Workshop Papers:
Synthetic Tumors Make AI Segment Tumors Better
Qixin Hu, Junfei Xiao, Yixiong Chen, Shuwen Sun, Jie-Neng Chen, Alan Yuille, Zongwei Zhou
NeurIPS Workshop 2022 | paper
When person re-identification meets changing clothes
Fangbin Wan, Yang Wu, Xuelin Qian, Yixiong Chen, Yanwei Fu
CVPR Workshop 2020 | paper | Highest Impact Award of IEEE Computer Society Biometrics Workshop
Preprint Papers:
Meissa: Multi-modal Medical Agentic Intelligence Yixiong Chen, Xin Bai, Yue Pan, Zongwei Zhou, Alan Yuille
Arxiv 2026 | paper
Are Vision Language Models Ready for Clinical Diagnosis? A 3D Medical Benchmark for Tumor-centric Visual Question Answering Yixiong Chen, Wenjie Xiao, Pedro RAS Bassi, Xinze Zhou, Sezgin Er, Ibrahim Ethem Hamamci, Zongwei Zhou, Alan Yuille
Arxiv 2025 | paper
Quality Sentinel: Estimating Label Quality and Errors in Medical Segmentation Datasets Yixiong Chen, Zongwei Zhou, Alan Yuille
Arxiv 2024 | paper
Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis
Xiaoshi Wu, Yiming Hao, Keqiang Sun, Yixiong Chen, Feng Zhu, Rui Zhao, Hongsheng Li
Arxiv 2023 | paper
X-IQE: eXplainable Image Quality Evaluation for Text-to-Image Generation with Visual Large Language Models Yixiong Chen, Li Liu, Chris Ding
Arxiv 2023 | paper
Rethinking Two Consensuses of the Transferability in Deep Learning Yixiong Chen, Jingxian Li, Chris Ding, Li Liu
Arxiv 2022 | paper
Talks
08/2025, Vision Language Understanding for Multi-time Point Chest X-Ray Images. Thanks Prof. Zongwei Zhou for the invitation.
06/2023, Meta-learning for adaptive fine-tuning. Thanks Dr. Zongwei Zhou for the invitation.
02/2023, The property of DNN's layer-wise convergence. Thanks Dr. Zongwei Zhou for the invitation.
Services
Reviewer of NeurIPS, ICLR, ICML, ECCV, MICCAI, TMI, MedIA, IJCV, and T-ASE.
Teaching assistant at CUHK (Shenzhen).
Awards
2024, Highest Impact Award of IEEE Computer Society Biometrics Workshop.
2023, Excellent Paper on Science and Technology of Shenzhen.
2022, Excellent Paper on Artificial Intelligence of Shenzhen.
2021, Second Class Scholarship for Outstanding Graduates of Fudan University.
2018, Huawei Cloud Scholarship.
2015, 1st prize of National Physics Competition of China.
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