Yale Chang
Senior Scientist at Philips
Cambridge, Massachusetts, United States
Summary
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Senior🎓
Top SchoolYale Chang is a Senior Scientist with 12 years of experience applying machine learning and deep learning to healthcare, translating research-grade models into clinical decision support systems deployed at scale. He has led multidisciplinary teams at Philips to build early warning systems—such as cardiogenic shock and hemodynamic instability predictors—that improved patient outcomes and appear in high-impact clinical journals. A PhD in machine learning from Northeastern, Yale has 20+ peer-reviewed ML and clinical papers and a strong track record in PhysioNet challenges, including a first-place solution for ECG-based cardiac abnormality detection. He combines expertise in time series, reinforcement learning, and causal inference to optimize treatments for acute conditions like sepsis and ARDS, and holds multiple patents related to clinical algorithms. Based in Cambridge, MA, he’s equally fluent in academic rigor and production deployment, often driving validation studies and trial design improvements that non-obviously bridge ML models to real-world hospital workflows.
12 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (PhD), Machine Learning, Doctor of Philosophy (PhD), Machine Learning at Northeastern UniversityBachelor of Engineering (B.E.), Electronic Engineering, Bachelor of Engineering (B.E.), Electronic Engineering at Tsinghua University
Chinese, EnglishGithub contributions (5)
yalechang/computer_vision
Feb 2014 - Apr 2014
Contributions:46 commits in 2 months
yalechang/COPDGene
Sep 2013 - Jan 2014
Contributions:63 commits in 3 months
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