CV

Last updated: August 2026

Research Profile

Medical multimodal foundation models, explainable medical AI, vision–language learning, generalist–specialist collaboration, and agentic clinical systems/Harnesses.

Education

The Hong Kong University of Science and Technology · Sep 2023–Present
Ph.D. in Computer Science and Engineering · Advisor: Prof. Hao Chen · GPA: 3.857/4.3

Tsinghua University · Sep 2020–Jul 2023
M.E. in Artificial Intelligence · GPA: 4.0/4.0 · Rank: 1/112

Hefei University of Technology · Sep 2016–Jul 2020
B.S. in Automation · GPA: 3.67/4.0 · Rank: 1/183

Experience

Research Intern, TGT Project, JD Health · Apr 2026–Present
Research and development of medical multimodal large language models and agent Harness systems for long-horizon clinical workflows.

FA Talent, AI4Science, Microsoft Research Asia · Jan–Jul 2023
Multimodal understanding with large language models.

Researcher, YouTu Lab, Tencent · Jul 2021–Jan 2023
Vision–language pretraining and multi-label classification.

Research Impact

• MedDr and GSCo: Co-developed an open-source medical generalist foundation model and a generalist–specialist collaboration framework. Paper · Code · HKUST feature
• ConceptCLIP: Co-first author of an explainable biomedical foundation model trained with 23 million image–text–concept triplets. Paper · Code
• SmartCare: Contributed to the medical foundation-model research underlying an end-to-end clinical AI platform. Project · HKUST Clinic pilot

First- and Co-first-author Publications

1. Sunan He*, Yuxiang Nie*, et al. “Towards Generalizable AI in Medicine via Generalist–Specialist Collaboration.” Nature Biomedical Engineering, 2026. Paper
2. Yuxiang Nie*, Sunan He*, et al. “An Explainable Biomedical Foundation Model via Large-Scale Concept-Enhanced Vision–Language Pretraining.” Nature Biomedical Engineering, 2026. Paper
3. Taolin Zhang*, Sunan He*, et al. “Vision–Language Pre-training with Object Contrastive Learning for 3D Scene Understanding.” AAAI, 2024.
4. Sunan He, Taian Guo, et al. “Open-Vocabulary Multi-Label Classification via Multi-modal Knowledge Transfer.” AAAI, 2023.

Co-authored Publications

1. Linshan Wu, Yuxiang Nie, Sunan He, et al. “A Universal Foundation Model for Grounded Biomedical Image Interpretation.” Nature Communications 17, 7173 (2026). Paper
2. Shu Yang et al., including Sunan He. “Large-Scale Self-Supervised Video Foundation Model for Intelligent Surgery.” npj Digital Medicine 9, 220 (2026). Paper
3. Ali Abdollahi et al., including Sunan He. “The Next Paradigm in Medical AI: A Survey of Agentic AI in Biomedicine.” IEEE Reviews in Biomedical Engineering, online ahead of print, 2026. Paper
4. Linshan Wu, Jiaxin Zhuang, Yanning Zhou, Sunan He, et al. “Large-Scale Generative Tumor Synthesis in Computed Tomography Images for Improving Tumor Recognition.” Nature Communications 16, 11053 (2025). Paper
5. Haibo Jin, Haoxuan Che, Sunan He, et al. “A Chain of Diagnosis Framework for Accurate and Explainable Radiology Report Generation.” IEEE Transactions on Medical Imaging, 2025.
6. Guanghao Meng, Sunan He, et al. “EvdCLIP: Improving Vision–Language Retrieval with Entity Visual Descriptions from Large Language Model.” AAAI, 2025.
7. Hanjun Li, Xiujun Shu, Sunan He, et al. “D3G: Exploring Gaussian Prior for Temporal Sentence Grounding with Glance Annotation.” ICCV, 2023.

Professional Service

Conference reviewer: CVPR 2026; ECCV 2026; NeurIPS 2026; AAAI 2026 and 2027; ACM Multimedia 2024.

Honors

• RedBird PhD Award, HKUST, 2023, 2025, and 2026
• Stars of Tomorrow Internship Program, Microsoft Research Asia, 2023
• Second-Class Scholarship, Tsinghua University, 2021
• National Scholarship, Ministry of Education, China, 2017–2019

* Equal contribution.