Kuan Chen is a data scientist with 11 years of experience at the intersection of AI and biomedical science, currently serving as a founding data scientist at Modella AI where he builds multimodal generative models for pathology images. His work contributed to a Nature 2024 paper on a multimodal AI copilot for human pathology and follows a sustained research trajectory at Harvard Medical School and the Broad Institute. Trained in computer science at Columbia and formerly a PhD student in Harvard Neurobiology, he bridges deep learning research and practical clinical image applications, including unsupervised tumor microenvironment quantification and novel H&E image representations. Known for translating cutting-edge models into tools that accelerate pathology workflows, he combines academic rigor with startup execution in Boston’s biomedical AI scene.
11 years of coding experience
3 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Columbia University
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