Associate Professor · Shenzhen University
Open Networks and Systems for Trustworthy Intelligence
My research sits at the intersection of networking, artificial intelligence, and cryptographic security. I study architectures, protocols, and trust mechanisms for open networks and systems, with a focus on efficient communication, trustworthy coordination, and verifiable computation. My current interests include blockchain and Web 3.0 infrastructure, trustworthy and verifiable AI, and multi-agent coordination in intelligent network systems.
I received my Ph.D. in Information Engineering from The Chinese University of Hong Kong in 2015, advised by Prof. Soung-Chang Liew. Before that, I earned my M.S. degree from Beijing University of Posts and Telecommunications in 2011 and my B.S. degree in Electronic Information Engineering from the University of Electronic Science and Technology of China in 2008.
From 2015 to 2016, I was a postdoctoral research fellow at the Institute of Network Coding of CUHK. I joined Shenzhen University in 2016, and I am currently an Associate Professor in the College of Electronics and Information Engineering. I am also affiliated with the Guangdong Provincial Social Science Research Base for FinTech and Digital Economy.
My long-term goal is to design new systems for next-generation information infrastructures rather than focus on isolated algorithms. Across these efforts, a recurring theme is open networks and systems for trustworthy intelligence: I study how architectures, protocols, and trust mechanisms can support efficient communication, trustworthy coordination, and verifiable computation in open environments, together with the design, implementation, and optimization of practical systems.
I study architectures, protocol design, and performance optimization for blockchain and Web 3.0 infrastructure in open networks, with the goal of enabling secure, scalable, and efficient identity management, collaborative services, value exchange, and data sharing without centralized trust.
I study how to make AI systems trustworthy, verifiable, and accountable in open collaborative environments, with particular interest in privacy-preserving learning, model verification, zero-knowledge proofs, and secure coordination mechanisms that can support reliable intelligent services.
I study coordination mechanisms for multi-agent and intelligent network systems in open and dynamic environments, and how sensing, decision-making, interaction, and adaptive optimization can improve system efficiency, robustness, and autonomy for real-time, trustworthy intelligent services.
* Corresponding author. # Equally contributing authors.