Haoping Bai
Machine Learning Research Engineer at Apple
Cupertino, California, United States
Summary
👤
Senior🎓
Top SchoolHaoping Bai is a Machine Learning Research Engineer based in Cupertino with nine years of experience applying ML to real-world problems at Apple. He pairs rigorous academic training—a perfect GPA from Carnegie Mellon (MS) and Georgia Tech (BS)—with hands-on engineering, contributing full-stack improvements to open-source tools like Scalabel to streamline visual data annotation workflows. At Apple he bridges research and production, shipping usable features and temporary back-end fixes that prioritize developer and annotator productivity. Known for attention to UI/UX detail (hotkey hints, quickdraw refinements) as well as practical data tooling (download and URL task support), he focuses on solutions that measurably make lives better.
9 years of coding experience
Bachelor's degree, Computer Science (Intelligence, Mod&Sim), Major GPA 4.00/4.00, Bachelor's degree, Computer Science (Intelligence, Mod&Sim), Major GPA 4.00/4.00 at Georgia Institute of TechnologyMaster of Science in Machine Learning, GPA 4.00/4.00, Master of Science in Machine Learning, GPA 4.00/4.00 at Carnegie Mellon University
English, Chinese, French
Github Skills (8)
javascript10
web-development10
front-end-development10
react9
back-end-development9
html9
go8
css8
Programming languages (4)
Github contributions (5)
scalabel/scalabel
Apr 2018 - Jan 2019
Scalabel: A versatile web-based visual data annotation tool
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:46 commits in 9 months
Contributions summary:Haoping primarily contributed to the front-end development of the Scalabel project, making several changes to the annotation interface. These changes included fixing various link issues within the monitor, adding hotkey hints, and refactoring and enhancing the quickdraw feature for improved usability. The user also made modifications to the back-end, including a temporary fix related to seg2d labeling, and implemented the download functionality for labeling data and task URLs.
data-annotationweb-basedvisual-dataannotation-toolversatile
bhpfelix/DNC-NumPy
Mar 2018 - Mar 2018
Contributions:92 commits, 88 pushes, 1 branch in 11 days
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