I am a dedicated researcher advancing AI in healthcare, with a particular focus on Medical Image Analysis and Trustworthy AI. Currently at Henry Ford Health, I explore innovative AI-driven healthcare solutions, specializing in medical image analysis and reliable AI systems. I hold a Ph.D. in Computer Science from Wayne State University, where my research has been published in top venues including MICCAI, WACV, NeurIPS, IJCAI, and ECML.

My research focuses on two main areas: Medical Image Analysis with Deep Learning (automatic medical image segmentation, multi-modal learning, foundation models in medical domain, clinical-oriented AI solutions for healthcare) and Trustworthy AI (fairness, explainability, robustness). I strive to bridge the gap between cutting-edge AI and practical healthcare applications. If you’re interested in Medical Image Analysis, or Trustworthy AI, please don’t hesitate to reach out—I’m eager to explore collaboration opportunities.

🔥 News

• 2025.02:  💼 I am serving as PC mebmber on IJCAI 2025.
• 2024.10:  🎉 Two papers accepted by WACV 2025.
• 2024.08:  💼 I start working at Henry Ford Health.
• 2024.07:  🎉 One Paper accepted by ECCV 2024.
• 2024.07:  🎉 I successfully defended my Ph.D. dissertation.
• 2024.04:  🎖 I won the Michael E. Conrad Award for 2023-2024 (sole recipient among graduate students in the Department of Computer Science, Wayne State University).
• 2023.12:  💼 I gave a talk on Medical Imaging Segmentation with AI at Karmanos Cancer Institute.
• 2023.12:  ✨ I passed my Ph.D. dissertation prospectus exam.
• 2023.11:  💼 I gave a talk on “Medical Image Segmentation with Transformers” at Wayne State University’s Computer Science Department.
• 2023.09:  🎖 I won the Department Oustanding GRA Award in the academic year 2022-2023.
• 2023.06:  🎉 One Paper accepted by MICCAI 2023.
• 2023.04:  🎉 One Paper accepted by IJCAI 2023.
• 2022.11:  🚁 I attended NeurIPS 2022 at New Orleans and illustrated our paper poster.
• 2022.11:  🎖 I won the Graduate Student Professional Travel Award.
• 2022.11:  🎉 One Paper accepted by AAAI 2023.
• 2022.09:  🎉 One Paper accepted by NeurIPS 2023.
• 2022.06:  🎉 One Paper accepted by ECML PKDD 2022.
• 2022.04:  🎉 One Paper accepted by IJCAI 2022.

📝 Publications

Full publications here

• [WACV 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, Chetty Indrin, Kundan Thind, and Dongxiao Zhu.

• [WACV 2025] AutoProSAM: Automated Prompting SAM for 3D Multi-organ Segmentation Chengyin Li, Prashant Khanduri, Yao Qiang, R. Ibn Sultan, Indrin Chetty, and Dongxiao Zhu.

• [MICCAI 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, and Dongxiao Zhu.

• [Medical Physics 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, and Indrin J. Chetty.

• [AAPM 2023] (Oral) 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, and Indrin J. Chetty.

• [ECML PKDD 2022] (Oral) Coupling User Preference with External Rewards to Enable Driver-centered and Resource-aware EV Charging Recommendation Chengyin Li, Zheng Dong, Nathan Fisher, and Dongxiao Zhu.

• [BIBM 2020] COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-rays Xin Li, Chengyin Li, Dongxiao Zhu.

• [ECCV 2024] Fairness-aware Vision Transformer via Debiased Self-Attention Yao Qiang, Chengyin Li, Prashant Khanduri, and Dongxiao Zhu

• [IJCAI 2023] Negative Flux Aggregation to Estimate Feature Attributions Xin Li, Deng Pan, Chengyin Li, Yao Qiang, and Dongxiao Zhu

• [NeurIPS 2022] Attcat: Explaining transformers via attentive class activation tokens Yao Qiang, Deng Pan, Chengyin Li, Xin Li, Rhongho Jang, and Dongxiao Zhu

• [IJCAI 2022] Counterfactual interpolation augmentation (CIA): A unified approach to enhance fairness and explainability of DNN Yao Qiang, Chengyin Li, Marco Brocanelli, and Dongxiao Zhu

📖 Educations

• 2019.09 - 2024.06, Doctor of Philosophy in Computer Science, Wayne State University
• 2013.09 - 2016.07, Master, Chinese Academy of Sciences
• 2009.09 - 2013.07, Bachelor, Nanjing University of Science and Technology

💻 Experience

• 2024.08 - Present, Researcher and Programmer, Henry Ford Health
• 2022.05 - 2024.07, Reaserch Scientist (part-time), Henry Ford Health
• 2019.09 - 2024.06, Graduate Research Assistant, Trustworthy AI Lab, Wayne State University
• 2017.09 - 2018.12, Visiting Student, The Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
• 2017.09 - 2018.09, Teaching Assistant, The Chinese University of Hong Kong (SZ)

📃 Teaching

• 2017 - 2018, Teaching Assistant for CSC 4800 Data Mining.

💼 Academic Service

• Conference Program Committee Member/Reviewer: IJCAI 2024-2025, NeurIPS 2023-2024, CVPR 2024-2025, MICCAI 2023-2024, ICML 2025, AISTATS 2025, ICLR 2025, ICCV 2025
• Journal Reviewer: IEEE Transactions on Medical Imaging, Transactions on Machine Learning Research (TMLR), Medical Physics, Scientific Reports, Smart Health, BMC Genomics, Journal of Medical Imaging

🎖 Honors and Awards

• Michael E. Conrad Award (Highest Honor at WSU CS Department), 2024
• Department Oustanding GRA Award, 2023
• Graduate Student Professional Travel Award, 2022
• Thomas C. Rumble Fellowship Award, 2019-2020

💼 CV

• PDF

🔗 Links

• 👨‍🏫 Ph.D. Advisors: Dongxiao Zhu