Department of Radiation Oncology, Henry Ford Health

Chengyin Li

AI Researcher in Medical Imaging, Adaptive Radiotherapy, and Foundation Models

My research develops deep-learning methods for medical image analysis, focusing on 3D CT/MR segmentation, adaptive radiotherapy, and medical foundation models.

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Chengyin Li

About

I am a researcher in AI for healthcare, working on medical image analysis. Since 2019, I have developed deep-learning methods that aim to be rigorous, generalizable, and clinically relevant, spanning multi-modal learning, medical foundation models, 2D/3D CT and MR segmentation, and adaptive radiotherapy. I currently work in the Department of Radiation Oncology at Henry Ford Health, where my research focuses on medical image analysis for radiation therapy.

I received my Ph.D. in Computer Science from Wayne State University, where I was advised by Prof. Dongxiao Zhu. My work has appeared at venues including CVPR, NeurIPS, ECCV, WACV, MICCAI, IJCAI, TMLR, and Medical Physics.

I am always glad to connect with others working on medical image analysis and clinical AI, so please feel free to reach out.

News

Recent updates

2026.05 Snap Oral accepted at the 2026 Joint AAPM|COMP Annual Meeting (Vancouver), to appear in Medical Physics.
2026.05 Paper accepted to TMLR: On Federated Compositional Optimization: Algorithms, Analysis, and Guarantees.
2026.02 WalkGPT accepted to CVPR 2026.
2026.01 Serving as PC member / reviewer for ICLR 2026, AAAI 2026, CVPR 2026, ICCV 2026, MICCAI 2026, and NeurIPS 2026.
2025.10 Presented GeoSAM at ECAI 2025 (Bologna, Italy).
2025.05 Oral at the 71st COMP Annual Scientific Meeting (ASM).
2025.04 Paper accepted to Medical Physics: Ensemble Loss Function Optimization.
2025.03 Paper accepted to IJCNN 2025: Interpretability-aware Vision Transformer.
2025.02 Named IEEE TMI Distinguished Reviewer (2024–2025).
2025.01 Invited as Guest Editor for JAIKE (Journal of Artificial Intelligence and Knowledge Engineering).
2024.10 Two papers accepted to WACV 2025: MulModSeg and AutoProSAM.
2024.08 Joined Henry Ford Health as Researcher & Programmer in Radiation Oncology.
2024.07 Successfully defended my Ph.D. dissertation at Wayne State University.
2024.07 Paper accepted to ECCV 2024: Fairness-aware Vision Transformer.
2024.04 Won the Michael E. Conrad Award (sole recipient among CS graduate students at Wayne State University).
2023.06 Paper accepted to MICCAI 2023: FocalUNETR.
2022.11 Paper accepted to NeurIPS 2022: AttCAT.
2022.06 Oral paper accepted to ECML-PKDD 2022.
2022.04 Paper accepted to IJCAI 2022.

Research

Areas of focus

01

Medical Image Segmentation & Foundation Models

2D/3D multi-organ and multi-modal CT/MR segmentation with transformer and SAM-style foundation models, including FocalUNETR, MulModSeg, and AutoProSAM.

02

Adaptive Radiotherapy & Clinical AI

Research on segmentation and registration methods for MRI-guided adaptive radiotherapy, drawing on prior-fraction information and robust modeling.

03

Robust & Reliable Deep Learning

Methods for fairness, explainability, and robustness that help deep models stay dependable in practice, such as FairViT and AttCAT.

Publications

Publications

My name is shown in red. See also Google Scholar and my CV.

  1. 2025
    MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Chengyin Li, Hui Zhu, Rafi Ibn Sultan, Hassan Bagher-Ebadian, Prashant Khanduri, Indrin Chetty, Kundan Thind, Dongxiao Zhu. WACV, 2025.
  2. 2025
    AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation Chengyin Li, Prashant Khanduri, Yao Qiang, Rafi Ibn Sultan, Indrin Chetty, Dongxiao Zhu. WACV, 2025.
  3. 2025
    Enhancing CT Image Segmentation Accuracy Through Ensemble Loss Function Optimization Chengyin Li, Rafi Ibn Sultan, Hassan Bagher-Ebadian, Yao Qiang, Kundan Thind, Dongxiao Zhu, Indrin J. Chetty. Medical Physics, 2025.
  4. 2024
    On the Implementation and Evaluation of Loss Functions for Robust Multiple Anatomy Segmentation on CT Images Chengyin Li, Rafi Ibn Sultan, Hassan Bagher-Ebadian, Yao Qiang, Kundan Thind, Dongxiao Zhu, Indrin Chetty. ICCR, 2024.
  5. 2023
    FocalUNETR: A Focal Transformer for Boundary-aware Prostate Segmentation using CT Images Chengyin Li, Yao Qiang, Rafi Ibn Sultan, Hassan Bagher-Ebadian, Prashant Khanduri, Indrin J. Chetty, Dongxiao Zhu. MICCAI, 2023.
  6. 2023
    A New Architecture Combining Convolutional and Transformer-Based Networks for Automatic 3D Multi-Organ Segmentation on CT Images Chengyin Li, Hassan Bagher-Ebadian, Rafi Ibn Sultan, Mohamed Elshaikh, Benjamin Movsas, Dongxiao Zhu, Indrin J. Chetty. Medical Physics, 2023.
  7. 2022
    Putting the ‘mi’ in Omics: Discovering miRNA Biomarkers for Pediatric Precision Care Chengyin Li, Rhea E. Sullivan, Dongxiao Zhu, Steven D. Hicks. Pediatric Research, 2022.
  8. 2020
    COVID-MobileXpert: On-device COVID-19 Patient Triage and Follow-up Using Chest X-rays Xin Li, Chengyin Li, Dongxiao Zhu. BIBM, 2020.
  9. 2026
    WalkGPT: Grounded Vision–Language Conversation with Depth-Aware Segmentation for Pedestrian Navigation Rafi Ibn Sultan, Hui Zhu, Xiao Zhou, Chengyin Li, Prashant Khanduri, Marco Brocanelli, Dongxiao Zhu. CVPR, 2026.
  10. 2025
    GeoSAM: Fine-tuning SAM with Sparse and Dense Visual Prompting for Automated Segmentation of Mobility Infrastructure Rafi Ibn Sultan, Chengyin Li, Hui Zhu, Prashant Khanduri, Marco Brocanelli, Dongxiao Zhu. ECAI, 2025.
  11. 2024
    Fairness-aware Vision Transformer via Debiased Self-Attention Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu. ECCV, 2024.
  12. 2022
    AttCAT: Explaining Transformers via Attentive Class Activation Tokens Yao Qiang, Deng Pan, Chengyin Li, Xin Li, Rhongho Jang, Dongxiao Zhu. NeurIPS, 2022.

Honors

Awards & recognition

  • 2024–2025 IEEE Transactions on Medical Imaging (TMI) Distinguished ReviewerRecognition for outstanding peer review at a flagship medical-imaging journal.
  • 2024 Michael E. Conrad Award, highest honor in the Wayne State University CS DepartmentSole recipient among graduate students.
  • 2024 Outstanding Graduate Research Assistant Award, Wayne State University
  • 2022 Graduate Student Professional Travel Award
  • 2019–2020 Thomas C. Rumble Fellowship Award

Peer Review & Service

Judging the work of others

I regularly evaluate submissions for the field's leading conferences and journals as a program-committee member, reviewer, and editor.

Editorial
Guest Editor, JAIKE: Journal of Artificial Intelligence and Knowledge Engineering (2025)
Program Committee & Conference Reviewer
CVPR 2024–2026·NeurIPS 2024–2026·MICCAI 2023–2026·IJCAI 2024–2026·WACV 2025–2026·ICCV 2025·ICML 2025·ECCV 2026·ICLR 2026·AISTATS 2025–2026·ECAI 2025·AAAI 2026
Journal Reviewer
Medical Physics 2024–2025·IEEE Trans. on Medical Imaging (TMI) 2023–2025·Trans. on Machine Learning Research (TMLR) 2024–2025·Computers in Biology and Medicine 2025·Journal of Medical Imaging 2024·Smart Health 2023·Scientific Reports (Nature) 2021
Invited Talks
“Medical Image Segmentation with Transformers”, Computer Science Seminar, Wayne State University 2024
“AI for Medical Image Segmentation”, BBC Virtual Seminar, Karmanos Cancer Institute 2024
Teaching
Graduate Teaching Assistant, Computer & Information Engineering, The Chinese University of Hong Kong (Shenzhen), 2017–2018

Education

  • 2019 – 2024Ph.D. in Computer ScienceWayne State UniversityAdvisor: Prof. Dongxiao ZhuDissertation: “Novel Transformer Architectures for 3D Multi-Modal and Multi-Organ Medical Image Segmentation”
  • 2013 – 2016M.E. in Chemical EngineeringUniversity of Chinese Academy of Sciences
  • 2009 – 2013B.E. in Chemical EngineeringNanjing University of Science and Technology

Experience

  • 2024 – PresentResearcher & Programmer, Radiation OncologyHenry Ford Health
  • 2022 – 2024Research Scientist (part-time), Radiation OncologyHenry Ford HealthMentor: Dr. Indrin J. Chetty
  • 2019 – 2024Graduate Research Assistant, Trustworthy AI LabWayne State UniversityAdvisor: Prof. Dongxiao Zhu
  • 2017 – 2018Visiting Student, Low-level Computer VisionShenzhen Institutes of Advanced Technology, CASMentor: Prof. Yu Qiao
  • 2017 – 2018Graduate Teaching AssistantThe Chinese University of Hong Kong (Shenzhen)