I am Kai Chen, a third-year PhD student in Computer Science at the University of Virginia, advised by Dr. Tianhao Wang. I obtained my Bachelor’s degree in Mathematics and Applied Mathematics at Zhejiang University, and earned a double major in Finance. I received my Master’s degree in Statistics with Data Science from the University of Edinburgh. Before starting my PhD studies, I spent about one and a half years working at ByteDance as a Data Analyst. In 2026, I was a Student Researcher at Google Research.
My research interests include differential privacy, generative AI, and AI security. I actively welcome any collaborators. If you are interested in differential privacy and its applications in data generation, please don’t hesitate to contact me.
🔥 News
- 2026.08: 🎉🎉 Our work Beyond One-Size-Fits-All: Neural Networks for Differentially Private Tabular Data Synthesis is accepted to CCS 2026.
- 2026.05: I join Google Research (Seattle) as a Student Researcher, leading a project on differentially private data insights.
- 2025.08: 🎉🎉 Our work Benchmarking Differentially Private Tabular Data Synthesis is accepted to SIGMOD 2026.
- 2025.04: 🎉🎉 Our work Benchmarking Differentially Private Tabular Data Synthesis is presented at ICLR Workshop 2025.
- 2024.08: I start my research in the University of Virginia, under the supervision of Dr. Tianhao Wang.
📖 Educations
- 2024.08 - (now), Ph.D. in Computer Science, University of Virginia
- 2020.09 - 2021.08, M.S. in Statistics with Data Science, University of Edinburgh
- 2016.09 - 2020.06, B.S. in Mathematics and Applied Mathematics & B.S. in Finance, Zhejiang University
📝 Publications
SHIP: Structured and Hierarchical Insight with Privacy (ArXiv Preprint)
K Chen, G Ni, A Cheu, K Fawaz, Y Hu, R McKenna, P Kairouz
Differentially Private Paired Table-Image Multimodal Synthesis (ArXiv Preprint)
K Chen, J Lamp, S Jha, T Wang
MRMMIA: Membership Inference Attacks on Memory in Chat Agents (ArXiv Preprint)
K Chen, Y Pang, T Wang
Beyond One-Size-Fits-All: Neural Networks for Differentially Private Tabular Data Synthesis (CCS 2026)
K Chen, C Gong, T Wang
Benchmarking Differentially Private Tabular Data Synthesis (SIGMOD 2026; ICLR Workshop 2025)
K Chen, X Li, C Gong, R McKenna, T Wang
Maximizing Time-aware Welfare for Mixed Items (ICDE 2022)
X Miao, H Peng, K Chen, Y Peng, Y Gao, J Yin
💻 Experience
- 2026.05 - 2026.09, Student Researcher, Google Research, Seattle, US. Led the private data insight project (SHIP).
- 2021.12 - 2023.05, Data Analyst, ByteDance, Shanghai, China. Douyin relation & privacy group.
📚 Service
- Reviewer @TDSC 2025
- Reviewer @VLDB Journal 2025
- Artifact Reviewer @SIGMOD 2025