Yechao Zhang
Research Fellow at Nanyang Technological University Singapore
Wuhan, Hubei, Singapore
Summary
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Senior🎓
Top SchoolYechao Zhang is a Research Fellow at the College of Computing and Data Science, Nanyang Technological University, with a Ph.D. in Cyberspace Security from Huazhong University of Science and Technology and nine years of professional experience. He has recent hands-on research internships at Tencent AI Lab and Ant Group, focusing on agent development and LLM security respectively, bridging academic rigor with practical AI safety work. His background centers on cybersecurity for AI systems, combining theoretical foundations from his doctoral studies with applied experimentation in industrial labs. Based in Wuhan and now working in Singapore, he brings a global perspective to threat modeling and secure AI deployment. Colleagues describe him as someone who moves smoothly between research design and prototype implementation, often uncovering subtle attack surfaces that others overlook.
9 years of coding experience
Doctor's Degree Cyberspace Security, Doctor's Degree Cyberspace Security at Huazhong University of Science and Technology
Github Skills (29)
spotify7
data-augmentation7
apple-music6
itunes6
adversarial-attacks6
music5
menubar5
cifar1004
paper4
deep-learning3
classification3
macos3
markdown3
large-language-models2
pre-trained-model2
Programming languages (3)
Github contributions (5)
CGCL-codes/AdvHash
Jul 2021 - Apr 2022
The official implementation of our ACM MM 2021 paper "AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial Patch".
Contributions:25 commits, 11 pushes, 1 branch in 9 months
CGCL-codes/TransferAttackSurrogates
Aug 2023 - Aug 2024
The official code of IEEE S&P 2024 paper "Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability". We study how to train surrogates model for boosting transfer attack.
Contributions:18 pushes, 1 branch, 1 comment in 1 year
adversarial-attacksadversarial-trainingblack-box-attackdata-augmentationdistribution-shift
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