Chun-hao Chang

Research Scientist at Meta

Seattle, Washington, United States
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Summary

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Senior
🎓
Top School
Chun-hao Chang is a Research Scientist at Meta and a PhD candidate in Computer Science at the University of Toronto, specializing in interpretable and robust machine learning with applications in healthcare. He brings 12 years of industry and research experience, combining deep expertise in ML models (CNNs, RNNs, deep Markov models, reinforcement learning) with production-grade software engineering in Python, C/C++, and Java. His background includes research internships at Google and Microsoft Research and hands-on ML engineering at Facebook’s ads ranking team, giving him a rare blend of academic rigor and applied system design. Chun-hao is skilled at turning clinical data into practical ML proofs-of-concept and building reusable, scalable architectures for complex workflows. Known for strong cross-functional communication, he excels at collaborating with non-technical stakeholders to drive impact in healthcare settings. Outside core research, he is an independent, fast learner who prioritizes interpretability and robustness when translating cutting-edge algorithms into real-world solutions.
code13 years of coding experience
job2 years of employment as a software developer
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Toronto
book國立臺灣大學
bookMaster of Science (MSc), Computer Science, Master of Science (MSc), Computer Science at 加拿大多倫多大學
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Github Skills (59)

python10
machine-learning10
attention-model10
generative-adversarial-network10
deep-learning10
gpu10
numpy9
autograd9
neural-network9
classifiers9
tensor9
gpu-acceleration9
convolution9
php8
media8

Programming languages (6)

C++PHPJupyter NotebookRubyPythonCuda

Github contributions (5)

github-logo-circle
zzzace2000/nodegam

Nov 2021 - Aug 2022

Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
Contributions:1 release, 37 commits, 38 pushes in 9 months
deep-learning
zzzace2000/FIDO-saliency

Jul 2018 - Apr 2022

Explaining Image Classifiers by Counterfactual Generation
Contributions:6 commits, 1 push in 3 years 9 months
classifiersmachine-learninginterpretabilitypytorch
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