Chun-sung Ferng
Software Engineer at Google
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolChun-sung Ferng is a seasoned software engineer with 11 years of experience in search, knowledge graphs, and machine learning, currently improving search algorithms at Google in the San Francisco Bay Area. He brings deep algorithmic problem-solving skills and fluency in Python, C/C++, and Java, grounded in strong academic training with an MS from National Taiwan University and further study at UIUC. His background spans production search features, knowledge extraction systems at Yahoo, and internationalization work for Google Assistant, reflecting both backend and client-side expertise. An active contributor to TensorFlow's neural-structured-learning tutorials and adversarial regularization code, he blends applied ML work with pragmatic engineering to ship reliable models and pipelines. Notably, he has a history of automating tedious workflows—from Sikuli scripts in public service to refactoring complex ML tutorials—showing a knack for improving developer productivity as well as end-user search quality.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science (B.S.), Computer Science and Information Engineering, 92.78/100, Bachelor of Science (B.S.), Computer Science and Information Engineering, 92.78/100 at National Taiwan UniversityChien-Kuo Senior High SchoolUniversity of Illinois Urbana-Champaign
Chinese, English, Hakka, Japanese
Stackoverflow
46reputation
6kreached
4answers
0questions
Github Skills (10)
keras10
machine-learning10
adversarial-learning10
tensorflow10
python9
documentation7
algorithm6
nsl6
javascript6
cleverhans6
Programming languages (2)
Github contributions (5)
tensorflow/neural-structured-learning
Sep 2019 - Dec 2022
Training neural models with structured signals.
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 11 reviews, 61 commits in 3 years 3 months
Contributions summary:Chun-sung primarily worked on refactoring and formatting the tutorial notebooks. They also made changes to the `AdversarialRegularization` class, addressing issues in metric computation and saving/loading models. The user further made changes that support PGD adversarial regularization.
adversarial-learningautoencodergraph-learningstructureddeep-learning
csferng/HashSGD
Oct 2014 - Nov 2014
Contributions:24 commits in 1 month
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