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Biography

Yi Zeng is a Ph.D. candidate at Virginia Tech, working with Prof. Ruoxi Jia. His research focuses on Security and Privacy issues related to top-notch AI and is sponsored by the Amazon Fellowship. In his recent study, he aims to theoretically and empirically safeguard advanced AI implementations, including both Computer Vision and Natural Language Processing.

Before that, he obtained his master’s degree in Machine Learning and Data Science at the Jacobs School of Engineering, University of California, San Diego, working with Prof. Farinaz Koushanfar. His undergraduate thesis, `Deep-Full-Range’, adopting deep learning for network intrusion detection, supervised by Prof. Huaxi Gu, was honored with the best degree paper award at Xidian University. Since 2018, he has started exploring security and privacy issues related to SOTA AI and closely worked with Prof. Han Qiu, Prof. Tianwei Zhang, and Prof. Meikang Qiu.

Activities

Works (2)

Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information

2023-11-15 | Conference paper
Contributors: Yi Zeng; Minzhou Pan; Hoang Anh Just; Lingjuan Lyu; Meikang Qiu; Ruoxi Jia
Source: check_circle
Crossref

Deep-Full-Range : A Deep Learning Based Network Encrypted Traffic Classification and Intrusion Detection Framework

IEEE Access
2019 | Journal article
Part of ISSN: 2169-3536
Source: Self-asserted source
Yi Zeng