Julie Jiang
Machine Learning Research Scientist at Meta
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolJulie Jiang is a machine learning research scientist with a PhD in computer science focused on computational social science, applying ML to study human behavior at scale for social good. With nine years of experience and internships across Google, Snap, ByteDance, Spotify and Bose, she blends rigorous academic research with product-aware applied ML, now contributing at Meta. A 2024 Forbes 30 Under 30 honoree and 2022 Snap Research Fellow, her work emphasizes empirical, ethically minded methods for online platforms and personalization. Based in San Francisco, she pairs strong theoretical grounding with hands-on experimentation in industry settings, often translating complex causal and behavioral insights into deployable models.
9 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Southern CaliforniaBS, Computer Science and Math, BS, Computer Science and Math at Tufts University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (27)
python10
data-science10
machine-learning10
ml10
deep-learning10
tensorflow10
deep-neural-networks10
neural-network10
segment10
theory9
cut9
graph9
graph-theory8
pytorch8
information-theory7
Programming languages (4)
Github contributions (5)
julie-jiang/julie-jiang.github.io
Aug 2018 - May 2024
Contributions:59 pushes, 1 branch in 5 years 9 months
julie-jiang/image-segmentation
Dec 2017 - Jul 2022
Utilize max-flow min-cut graph theory to segment images into foreground and background pixels
Contributions:16 commits, 17 pushes, 2 branches in 4 years 8 months
graph-cutsegment-imagespixelscuttheory
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