Department of Radiology
NYU Grossman School of Medicine
Email: ys1001 at nyu dot edu
My research focuses on creating label-efficient and explainable deep learning models for medical imaging to improve clinical workflow and patient care.In particular, I am excited about exploring the following directions:
- Multimodal learning: How can we efficiently integrate information from different modalities (e.g. imaging, text, tabular data, sequential data) to better inform clinical decisions?
- Explainable AI: Can we enable computer aided diagnosis systems to explain their reasoning in a way that mimics how humans communicate?
- Human-AI collaboration: What is the optimal way to present an AI’s diagnosis to clinicians so they can collaborate effectively to maximize patient outcomes?
I received my Ph.D. at the NYU Center for Data Science, advised by Prof. Krzysztof J. Geras and Prof. Kyunghyun Cho. Prior to joining NYU, I worked at Two Sigma Investments. I hold a Bachelor’s degree in Computer Science from Rice University.
Perspective students: Starting in Fall 2026, I am looking for highly motivated Ph.D. students to join my research group. You may apply through NYU Data Science PhD (see the medical AI track) or the Biomedical Imaging & Technology PhD at the NYU Vilcek Institute. For more details, please check out my advising statement . I’m also open to collaborations with predoctoral researchers and visiting scholars. If you are interested in working with me, please drop me an email.
Our work explores exciting frontiers in AI and medical imaging, including:
- Developing multi-modal deep learning models that integrate medical imaging (across multiple modalities) with clinical data such as EHRs and lab results.
- Designing counterfactual deep learning approaches to optimize diagnostic and treatment pathways.
- Building AI systems for video analysis, with applications such as understanding infant psychology development.
news
| May 6, 2026 | Our paper, Leveraging Fine-Tuned Large Language Models for Interpretable Pancreatic Cystic Lesion Feature Extraction and Risk Categorization, was published in the American Journal of Roentgenology. |
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| May 1, 2026 | Our paper, Deep learning-based prediction of acute pancreatitis severity from abdominal CT with multicenter external validation, was published in the Radiology Advances. |
| Apr 1, 2026 | Three papers from our lab on pancreatic imaging and pancreatic cystic lesions were accepted: two in Abdominal Radiology—Patient and lesion characteristics associated with follow-up completion for pancreatic cystic lesions detected on MRI and Automated report-based tracking of pancreatic cysts: implications for guideline-defined growth classification—and one in Pancreas, Pancreatic MRI Findings in High-Risk Individuals Compared with Matched Average-Risk Individuals. |
| Feb 1, 2026 | I will serve as the Communications Chair for Machine Learning for Healthcare (MLHC) 2026. Looking forward to seeing you in Baltimore this August! |
| Dec 24, 2025 | Our paper, Evaluating Generative Artificial Intelligence as an Educational Tool for Radiology Resident Report Drafting, was published in the Journal of the American College of Radiology. |
| Dec 1, 2025 | RSNA 2025 Highlights: Eight abstracts from our lab were presented at RSNA 2025. Our work on multimodal AI for breast cancer diagnosis was featured by AuntMinnie. In addition, our neuroradiology work received the RSNA 2025 Kuo York Chynn Neuroradiology Research Award. |
| Sep 12, 2025 | My research has been supported by an NIH UF1 Multi-Year Funded Research Project Cooperative Agreement Grant. |
| Sep 2, 2025 | I recevied the 2025 Milstein Pilot Project Fund. |
| Aug 12, 2025 | I received an NIH Research Project (R01) Grant. |
| Jun 6, 2025 | I gave an invited talk at IBDW 2025 . |
selected publications
2026
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Leveraging Fine-Tuned Large Language Models for Interpretable Pancreatic Cystic Lesion Feature Extraction and Risk CategorizationAmerican Journal of Roentgenology, 2026
2025
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Evaluating Generative AI as an Educational Tool for Radiology Resident Report DraftingJournal of the American College of Radiology, 2025
2024
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Burextract-llama: An llm for clinical concept extraction in breast ultrasound reportsIn Proceedings of the 1st International Workshop on Multimedia Computing for Health and Medicine, 2024
