Jingbo Yang
Quantitative Minion
United States
Summary
👤
Senior🎓
Top SchoolJingbo Yang is a machine-learning-focused software engineer with 11 years of experience, currently applying quantitative research and trading strategies at Citadel Securities while completing an MSCS on the AI track at Stanford. His work spans deep learning for healthcare — including EEG-based depression research and chest x‑ray analysis — as well as production-focused data engineering and FX strategy development. He has a strong engineering foundation from an Engineering Science degree at University of Toronto and hands-on systems experience from internships at Intel and Citadel, plus two years designing rockets with the University of Toronto Aerospace Team. Comfortable moving between research and production, Jingbo combines rigorous experimental work with pragmatic software design to turn models into deployable systems. An under-the-radar strength is his cross-domain curiosity: signal processing, differential privacy, and aerospace projects all inform his approach to robust ML systems.
11 years of coding experience
5 years of employment as a software developer
Bachelor's Degree, Engineering Science, Bachelor's Degree, Engineering Science at University of TorontoMaster's degree, Computer Science, Master's degree, Computer Science at Stanford University
Github Skills (3)
jekyll6
deep-learning1
artificial-intelligence1
Programming languages (2)
Github contributions (5)
stanfordmlgroup/MoCo-CXR
Apr 2021 - Jan 2022
Contributions:8 commits, 7 pushes, 1 branch in 8 months
JingboYang/SimpleAudioRecognition
Mar 2018 - Apr 2018
Contributions:27 pushes, 1 branch in 1 month
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