Minxing Zhang 张敏行

Ph.D. Student  ·  Computer Science  ·  Duke University

I am a third-year Ph.D. student in Computer Science at Duke University, advised by Dr. Jian Pei. Before joining Duke, I completed my undergraduate studies at Emory University, where I was advised by Dr. Li Xiong and Dr. Liang Zhao.

My research focuses on trustworthiness in AI models — particularly privacy and generalizability in large language models and LLM-based agents — with applications in data markets and spatio-temporal data mining. I am currently exploring LLMs and LLM-based agents from a conversation-level perspective, including high-quality conversation generation and evaluation, as well as privacy-preserving model performance estimation.

I am open to research collaborations and internship opportunities. I have always believed that words are the gentlest way to connect — perhaps we are in different cities, looking at different skies, living entirely different lives, but through a single message, we can briefly step into each other's world. Feel free to reach out. I hope we can be friends.

LinkedIn Google Scholar
Minxing Zhang
Summer 2025

Research Intern

AT&T Chief Data Office  ·  Bedminster, NJ
Summer 2022

DataThink Project

Microsoft & Emory University  ·  Atlanta, GA
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Minxing Zhang*, Y. Yang*, Z. Jia, X. Yang, J. Pei, Y. Zang, X. Deng, and X. Chen, "MPCEval: A Benchmark for Multi-Party Conversation Generation." arXiv preprint, 2026. arXiv
2
Minxing Zhang, Y. Yang, R. Xie, B. Dhingra, S. Zhou, and J. Pei, "Generalizability of Large Language Model-Based Agents: A Comprehensive Survey." ACM Computing Surveys, Feb. 2026. DOI
3
Z. Cui*, Minxing Zhang*, and J. Pei, "Learning to Attack: Uncovering Privacy Risks in Sequential Data Releases." arXiv preprint, 2025. arXiv
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Z. Cui*, Minxing Zhang*, and J. Pei, "On Membership Inference Attacks in Knowledge Distillation." arXiv preprint, 2025. arXiv
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Minxing Zhang and J. Pei, "Protecting Data Buyer Privacy in Data Markets." IEEE Internet Computing, vol. 28, no. 4, pp. 14–20, 2024. DOI
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Minxing Zhang, H. Lin, S. Takagi, Y. Cao, C. Shahabi, and L. Xiong, "CSGAN: Modality-Aware Trajectory Generation via Clustering-Based Sequence GAN." IEEE MDM 2023, pp. 148–157. DOI
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Minxing Zhang, D. Yu, Y. Li, and L. Zhao, "Deep Spatial Prediction via Heterogeneous Multi-Source Self-Supervision." ACM Transactions on Spatial Algorithms and Systems, vol. 9, no. 3, 2023. DOI
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Minxing Zhang, D. Yu, Y. Li, and L. Zhao, "Deep Geometric Neural Network for Spatial Interpolation." ACM SIGSPATIAL 2022. DOI