Zhiyi Chen
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Ph.D. Student Office: Klaus Advanced Computer Building, room 3337 Email: zchen798 AT gatech DOT edu |
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About Me
I am a third year Ph.D. Candidate in Computer Science at Georgia Tech, advised by Prof. Alberto Dainotti. I am interested in intersection of machine learning and Internet measurement. Before joining Georgia Tech, I received my bachelor’s degree in Department of Computer Science and Technology, Tsinghua University in 2020. CV
Research Interests
Application of machine learning in data science
Internet measurement
Cybersecurity
News
Jun, 2023: I started a research summer internship at Coalition, Inc.
Mar, 2023: I posted an APNIC Blog about my work on improving the inference of sibling Autonomous Systems. APNIC Blog
Feb, 2023: The joint work with Peng Li on DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data was accepted by the The ACM Special Interest Group on Management of Data (SIGMOD) 2023.
Feb, 2023: I presented a lightning talk on Improving the Inference of Sibling Autonomous Systems at NANOG 87 in Atlanta. The recording can be found at NANOG Talk.
Jan, 2023: My work Improving the Inference of Sibling Autonomous Systems was accepted by the Passive and Active Measurement Conference (PAM) 2023. Our dataset won the Best Community Artifact Award. (PDF, Dataset, Video)
Jul, 2022: I presented a talk Mapping ASNs to Organizations at MapKIT Workshop 2022.
Aug, 2021: I joined Georgia Tech as a Ph.D. student.
Jun, 2021: My work Principal Gradient Direction and Confidence Reservoir Sampling for Continual Learning was accepted at 30th International Conference on Artificial Neural Networks (ICANN) 2021.
Publications
[1] Improving the Inference of Sibling Autonomous Systems
Zhiyi Chen, Zachary S. Bischof, Cecilia Testart, Alberto Dainotti, PAM 2023
[2] DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data
Peng Li, Zhiyi Chen, Xu Chu, Kexin Rong, SIGMOD 2023
[3] Principal Gradient Direction and Confidence Reservoir Sampling for Continual Learning
Zhiyi Chen, Tong Lin, ICANN 2021