CV

You can download my resume here.

Education

• Duke University, Durham, North Carolina, USA, 2023 -
  Ph.D. Candidate, Vision and Image Processing Lab, Department of Biomedical Engineering
  • GPA: 3.84/4.0
• Shanghai Jiao Tong University (SJTU), Shanghai, China, 2019 - 2023
  Bachelor’s Degree of Engineering, major in Biomedical Engineering, minor in Computer Science and Engineering
  • GPA: 3.84/4.3 (Top 10%)
  • See more on my final transcript

Scholar experience

• Aug. 2023 – Present: VIP Lab @ Duke directed by Sina Farsiu

  A knowledge-enhanced multi-modality clinical assessment system for integrative analysis of textual and visual features

  • Developed a knowledge-enhanced multimodal clinical assessment framework integrating structured patient metadata and unstructured clinical text to support LLM-based clinical decision-making.
  • Built an expert-curated medical knowledge base using Retrieval-Augmented Generation (RAG) to improve domain-specific language understanding and reasoning.
  • Integrated imaging and textual representations via multimodal LLMs to model cross-modality relationships and improve diagnostic performance.
  • Abstract accepted by ARVO 2026; journal manuscript in preparation.

  A multi-granularity language learning approach to boost visual understanding

  • Proposed a novel contrastive learning framework enabling joint multi-label and cross-granularity alignment for medical image understanding.
  • Designed multi-granular learning objectives to improve representation consistency across label hierarchies.
  • Constructed large-scale multi-granular retinal and X-ray image-text datasets for systematic evaluation.
  • Accepted by ICLR 2026; available on arXiv.

  An Automated Quantitative Ulcer Analysis (AQUA) algorithm to classify Microbial keratitis (MK) organism types

  • Proposed a contrastive-learning-based approach to extract robust representations across heterogeneous clinical data patterns.
  • Developed a triple-stage multimodal framework to integrate imaging, metadata, and clinical features for organism-type classification.
  • Journal manuscript in preparation (expected 2026).

• Dec. 2022 – Jun. 2023: IMIT @ SJTU directed by Lichi Zhang

  A 2D/3D Registration Method for Full-length Images of Lower Limbs

  • Developed a learning-based 2D-3D registration network for full-length lower-limb X-ray and CT images.
  • Incorporated shifted-window self-attention and cross-attention mechanisms to improve feature extraction efficiency.
  • Proposed SigmoidDiceLoss to enable differentiable optimization for discrete anatomical labels.
  • Chinese patent submitted (under review).

• June. 2022 – Nov. 2022: CCVL @ JHU directed by Alan Yuille & VLAA @ UCSC directed by Yuyin Zhou & Cihang Xie

  Multi-view MAE for 3D medical image representation learning

  • Proposed the first multi-view framework for self-supervised 3D medical image representation learning.
  • Achieved performance comparable to state-of-the-art methods with substantially reduced training cost.
  • Published in MICCAI 2023 (Oral Presentation).

• Feb. 2022 – Jan. 2023: Advanced MRI Lab @ SJTU directed by Hongjiang Wei

  Brain Region Segmentation and Age Estimation Using QSM

  • Developed a novel segmentation network for key brain regions on QSM images to support brain age estimation.
  • Improved brain age prediction accuracy compared to prior T1-weighted MRI-based approaches.
  • Published in ISMRM 2023 and IEEE Journal of Biomedical and Health Informatics (JBHI).

Publications

2026

Z Li¹, Y Wang¹, S Farsiu, P Kinahan. Boosting Medical Visual Understanding From Multi-Granular Language Learning. The Fourteenth International Conference on Learning Representations (ICLR).

Y Wang, C He, LM Niziol, M Pawar, M Lu, MA Woodward, & S Farsiu. Large-Language-Model-Enhanced Multi-Modal Subtype Diagnosis of Microbial Keratitis on Slit-Lamp Photographs and Metadata. Association for Research in Vision and Ophthalmology (ARVO) 2026 Annual Meeting.

J Ong, MC Lu, C Thanitcul, M Pawar, JN Hart, EL Vogt, C Deng, S Farsiu, Y Wang, P Dmitriev, A Gupta. Deep Learning-Based Classification of Slit-Lamp Photograph Quality in Microbial Keratitis. Ophthalmology Science. 2026 Jan 21:101086.

2025

Z Li¹, Y Wang¹, S Farsiu, P Kinahan. Large‑scale data harmonization of radiology studies via multigranular vision‑language alignment. SPIE Medical Imaging 2026.

J Ong, M Lu, C Thanitcul, M Pawar, JN Hart, E Vogt, S Farsiu, Y Wang, P Dmitriev, A Gupta, N Nallasamy & MA Woodward. Automated Deep Learning Classification of the Quality of Slit-Lamp Photographs of Microbial Keratitis. Investigative Ophthalmology & Visual Science, 66(8), 4436-4436.

Z Yang, MA Woodward, LM Niziol, M Pawar, NV Prajna, A Krishnamoorthy, Y Wang, M Lu, S Selvaraj, & S Farsiu. Self-knowledge distillation-empowered directional connectivity transformer for microbial keratitis biomarkers segmentation on slit-lamp photography. Medical Image Analysis, 102, 103533.

2023

M Chen¹, Y Wang¹, Y Shi¹, J Feng, R Feng, X Guan, … & H Wei. Brain Age Prediction Based on Quantitative Susceptibility Mapping Using the Segmentation Transformer. IEEE Journal of Biomedical and Health Informatics.

Y Wang¹, Z Li¹, J Mei¹, Z Wei¹, L Liu, C Wang, … & Y Zhou. SwinMM: Masked Multi-view with Swin Transformers for 3d Medical Image Segmentation. 2023 International Conference on Medical Image Computing and Computer-Assisted Intervention. (pp. 486-496). Cham: Springer Nature Switzerland.

Y Wang, Y Shi, H Wei. A Brain Age Estimation Network based on QSM using the Segment Transformer. 2023 International Society for Magnetic Resonance in Medicine (ISMRM).

Awards

• 2025 Oral Presentation at SPIE 2026
• 2023 Oral Presentation at MICCAI 2023
• 2023 Outstanding Graduate of Shanghai Jiao Tong University
• 2022 Scholarship of School of Biomedical Engineering Alumni Association
• 2022 Merit Student of Shanghai Jiao Tong University
• 2021 Shanghai Municipal Government Scholarship
• 2020 Class A Scholarship of Shanghai Jiao Tong University

Service

• Conference Reviewer MICCAI 2025; MICCAI 2024;
• Journal Reviewer Image and Vision Computing; IEEE Journal of Biomedical & Health Informatics (JBHI);