关于
Aiden Gu (also Yu Gu) is a Principal Applied Scientist at Microsoft Research and Health & Life Science, where he works at the intersection of artificial intelligence, healthcare, and scientific discovery. His research focuses on large language models, multimodal foundation models, and agentic reasoning frameworks that enable real-world impact across health and science.
His work has been published in Nature, Science, and Cell, as well as leading AI conferences including ICLR, NeurIPS, and CVPR. Before joining Microsoft, he co-founded an AI startup focused on clinical data understanding that achieved a Series C acquisition.
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BiomedParse: A foundation model for smarter, all-in-one biomedical image analysis
BiomedParse reimagines medical image analysis, integrating advanced AI to capture complex insights across imaging types—a step forward for diagnostics and precision medicine.
GigaPath: Whole-Slide Foundation Model for Digital Pathology
Digital pathology helps decode tumor microenvironments for precision immunotherapy. In joint work with Providence and UW, we’re sharing Prov-GigaPath, the first whole-slide pathology foundation model, for advancing clinical research.
Domain-specific language model pretraining for biomedical natural language processing
COVID-19 highlights a perennial problem facing scientists around the globe: how do we stay up to date with the cutting edge of scientific knowledge? In just a few months since the pandemic emerged, tens of thousands of research papers have…