Bolun Wang
Engineering Manager at ByteDance
Shanghai, Shanghai, China
Summary
👤
Senior🎓
Top SchoolBolun Wang is an engineering manager at ByteDance who leads teams protecting TikTok’s Community Health, bringing a decade of experience at the intersection of security, systems, and machine learning. He holds a PhD in Computer Science from UC Santa Barbara, where his research exposed vulnerabilities in deep learning and devised defenses to secure DL systems—work that informs his pragmatic approach to risk and abuse detection in production. Before management he was an applied researcher and engineer at Facebook focused on detecting unauthorized scraping, and he has internship experience at Microsoft Research Asia analyzing mobile user behavior. Comfortable moving between research and production, he combines academic rigor with product-minded delivery to harden large-scale platforms against novel adversarial threats.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at UC Santa BarbaraBachelor of Science (BS) Electronic Engineering, Bachelor of Science (BS) Electronic Engineering at Tsinghua UniversityExchange Student Computer Science, Exchange Student Computer Science at University of ChicagoHong Kong University of Science and Technology (HKUST)
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (17)
pytorch10
python10
data-science10
machine-learning10
keras10
deep-learning10
security9
tensorflow9
jax9
transfer-learning9
trojan8
adversarial-machine-learning8
vulnerability7
neural-network5
ettercap5
Programming languages (2)
Github contributions (5)
bolunwang/backdoor
Nov 2018 - Oct 2019
Code implementation of the paper "Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks", at IEEE Security and Privacy 2019.
Contributions:14 commits, 1 push, 9 comments in 11 months
neural-networksecuritypythonkerasdeep-learning
bolunwang/translearn
Jul 2018 - Nov 2018
Code implementation of the paper "With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning", at USENIX Security 2018
Contributions:20 commits, 3 pushes, 4 comments in 4 months
securitytransfer-learningvulnerabilitypythonkeras
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