Zhengwei Tong

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I am a PhD student in the Computer Science Department at Duke University, advised by Prof. Kartik Nayak and Prof. Saba Eskandarian at UNC-Chapel Hill.

Previously, I obtained my Master’s degree in Mathematics from UW-Madison in 2023 and my Bachelor’s degree in Mathematics, with a minor in French, from the Wen-Tsun Wu Honors Class at Shanghai Jiao Tong University in 2022.

My research interest lies at the intersection of applied cryptography, decentralized systems, and economic security. I aim to build privacy-preserving and economically robust infrastructure for decentralized environments such as blockchains and peer-to-peer networks.

My recent work spans privacy-preserving inclusion lists, reputation-based P2P systems, and AI safety benchmarking. Currently, I am expanding my focus to the economic security of DeFi, exploring how mechanism design influences the stability and efficiency of decentralized financial protocols.

Feel free to reach out via email for collaboration.

Current Teaching

  • 2026 Fall (current) — CS 354/584, Duke University, Teaching Assistant

News

Jul, 2026 I’ve started my internship at Nethermind.
Jul, 2026 Our paper Privacy-Preserving Inclusion Lists has been accepted at AFT 2026!
Jun, 2026 I attended the CASA Summer School 2026 on Cryptography and Distributed Computing in Bochum, Germany.
Jun, 2026 I presented our work Persistent BitTorrent Trackers at the IC3 Blockchain Summer Camp 2026.
May, 2026 Our paper Persistent BitTorrent Trackers has also been accepted at SBC 2026!

Research

  1. pbts.png
    Persistent BitTorrent Trackers
    François-Xavier Wicht, Zhengwei Tong, Shunfan Zhou, Hang Yin, and Aviv Yaish
    In 2026 IEEE 11th European Symposium on Security and Privacy (EuroS&P), 2026
    Also presented at the Science of Blockchain Conference (SBC’26)
  2. ppil.png
    Privacy-Preserving Inclusion Lists
    Zhengwei Tong, Saba Eskandarian, and Kartik Nayak
    In Proc. 8th Conference on Advances in Financial Technologies (AFT 2026), 2026
  3. mj-bench.png
    MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
    Zhaorun Chen, Zichen Wen, Yichao Du, Yiyang Zhou, Chenhang Cui, Siwei Han, Zhenzhen Weng, Chaoqi Wang, Zhengwei Tong, Leria Huang, Canyu Chen, Haoqin Tu, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, and Huaxiu Yao
    In NeurIPS 2025 Datasets and Benchmarks Track, 2025
    Poster

Teaching Experience