Retrospective Lung-RADS v2022 Characterization of Fatal Lung Cancer Cases in the National Lung Screening Trial
Journal Academic Radiology, 2026
I graduated from UC Berkeley with a degree in Electrical Engineering & Computer Science in 2024. I currently work as a deep learning researcher in the Sohn Lab at UCSF, where I collaborate with doctors, engineers, and industry partners to improve diagnostics through imaging and big data. My current technical interests revolve around AI post-training reliability, uncertainty, and safety within mostly LLMs. I've also worked on foundation models, longitudinal modeling, and risk analyses across multimodal inputs (EHR & CT/XR/MRI).
October 3, 2026 Four of our works ranging on topics of homomorphic encryption, LLM uncertainty quantification, robustness, and reliability (hallucination, contradictions, + other bizarre errors) are accepted to two NeurIPS workshops in Sydney, Australia!
July 23, 2026 Excited to present our work at COLM in the LLM/VLM Deployment Opportunities and Risks in Healthcare workshop!
July 22, 2026 Our work was accepted to RSNA as oral and poster presentations on time-conditioned growth and morphological predictions of subsolid nodules!
Journal Academic Radiology, 2026
Conference NeurIPS | GenAI4Health Workshop, 2026
Conference NeurIPS 2026 | GenAI4Health Workshop
Conference NeurIPS 2026 | GenAI4Health Workshop
Conference COLM 2026 | LLM/VLM Deployment in Healthcare
Conference NeurIPS 2026 | WiML + GenAI4Health Workshop
Manuscript In revision
Conference RSNA 2026 | Oral & poster
Manuscript In submission
Conference RSNA 2025 | Poster
Manuscript In revision
Manuscript In revision
Manuscript Journal of Magnetic Resonance Imaging, 2026
Conference Conference on AI in Medical Imaging 2025 | Poster
Manuscript Journal of Imaging Informatics in Medicine, 2026
Conference Frontiers in Computational Precision Health 2026 + Society of Imaging Informatics in Medicine 2026
Manuscript BMC Medical Imaging, 2025
Conference UCSF Radiology Imaging Symposium 2023
Manuscript UC Berkeley Deep Learning Course 2023 [code, slides]
Conference Radiological Society of North America Annual Meeting, 2023
Manuscript medRxiv, 2023
Conference RSNA 2023
Manuscript medRxiv, 2022 [code]