My name is Chunyang Tang (唐春洋). I am a PhD student at College of AI, Tsinghua University advised by Prof. Qionghai Dai (戴琼海). My current research focuses on AI for ophthalmology, particularly developing algorithms for detecting subtle lesions in fundus images. I also work on translating advanced machine learning methods into clinically meaningful systems that can operate reliably in real-world environments.
I am broadly interested in the evolving landscape of large-scale AI, including foundation models, LLMs, diffusion models, and multimodal vision–language architectures. I am particularly curious about their adaptation, alignment, and robustness in real-world domains.
Previously, I worked on photoelectronic computing and diffractive neural networks (D²NN), investigating optical approaches to computation. These experiences shaped my long-term interest in the relationship between computational architecture and intelligent behavior.
Tao Yan, Di Zhang, Luxiao Chen, Taizhangtian Ma, Chunyang Tang, et al.
Early lessons from AI-TEC on data quality, clinical workflows, and clinician feedback when bringing AI agents into ophthalmic care.
Yitong Chen, Guoqiang Yang, Tao Yan, Chunyang Tang, Jiamin Wu, Qionghai Dai
A review of photonic computing platforms and the materials, fabrication, and integration requirements for practical AI and scientific computing.