Shali Jiang
Research Scientist at Meta
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolShali Jiang is a research scientist at Meta with a Ph.D. in Computer Science and a decade of experience applying Bayesian machine learning, active learning, and Bayesian optimization to ads ML modeling. Her doctoral work on efficient nonmyopic sequential experimental design informs practical ML solutions for large-scale systems, and she has hands-on industry experience from internships at Facebook and Google and engineering work at Baidu. Based in Sunnyvale, she bridges rigorous academic research with production-focused experimentation to improve model training and decision-making in advertising. Colleagues can expect a methodical researcher who translates probabilistic modeling advances into measurable product impact.
10 years of coding experience
5 years of employment as a software developer
Bachelor of Engineering (B.E.) Computer Science, Bachelor of Engineering (B.E.) Computer Science at Tianjin UniversityDoctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at Washington University in St. Louis
Github Skills (46)
python10
acceleration10
machine-learning10
numpy10
bayesian10
deep-learning10
tensorflow10
gpu10
autograd10
neural-network10
tensor10
gpu-acceleration10
optimization10
data-science9
pytorch9
Programming languages (4)
Github contributions (5)
shalijiang/efficient_nonmyopic_active_search
Apr 2019 - Nov 2019
Contributions:18 commits, 6 pushes in 7 months
shalijiang/pytorch
Jul 2019 - Aug 2019
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:16 pushes, 3 branches in 13 days
pythongpu-accelerationdeep-learninggpuacceleration
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