About me

Short Bibliography

I’m currently a Ph.D. student in the Department of Computer Science at North Carolina State University, working with Professor Yuchen Liu. I obtained my BS and MS degree both from the Department of Electrical and Computer Engineering at The Ohio State University, supervised by Professor Jia (Kevin) Liu. I am broadly interested in building trustworthy and intelligent wireless netowrk and communications with advanced techniques, including federated learning, digital twins, reinforcement learning, etc.

Research Interests

My research pursuits are rooted in the confluence of wireless networks, machine learning, and mobile computing, each bearing the potential to profoundly impact modern technological landscapes. In the sphere of networking and systems, I delve into exploring wireless technologies, envisioning new network architectures, developing protocols, investigating digital twins, and fortifying security measures. Transitioning into machine learning, my focus broadens to harnessing generative AI, fostering self-awareness systems, and employing data analytics to enhance networking, sensing, and security paradigms. The realm of mobile computing beckons with opportunities in infrastructure mobility, employing Unmanned Aerial Vehicles (UAVs), and orchestrating robotic networked systems.

  • Network Digital Twins: Mapping Next Generation Wireless Networks into Digital Reality
  • Trustworthy Distributed Mapping for Network Digital Twins
  • Design of Predictive Mobile and Wireless Network Systems Using Machine Learning


[05/24] A paper on digital twin-assisted caching optimization has been accepted by JSAC-SI-OPT’24 special issue.

[04/24] Two papers on network digital twin and federated learning poisoning attacks have been accepted by IFIP/IEEE Networking 2024.

[04/24] A paper on Byzantine-resilient decentralized federated learning has been accepted by ACM CCS 2024 (acceptance rate: 19%).

[03/24] Received Graduate Merit Award (GMA) provided by the College of Engineering.

[12/23] A paper on multi-agent reinforcement learning policy evaluation with local TD-learning updates is accepted by ACM AAMAS 2024 (acceptance rate: 25%).

[08/23] Joined the NICE Lab at NC State as a Ph.D. student.