Ruozhou Yu
Bio
Ruozhou Yu is an assistant professor in the Department of Computer Science at NC State University. His research focuses on computer networks, distributed systems and cybersecurity, with an emphasis on designing high-performance, secure and practical systems for smart and connected communities. His work spans the Internet of Things, cloud and edge computing, satellite computing and networks, wireless and mobile networks, data analytics and machine learning, blockchain and quantum networking. His long-term goal is to advance both the theoretical foundations and practical impact of large-scale connected systems through algorithm design, game theory, optimization and provable security.
Education
Ph.D. Arizona State University 2019
B.S. Beijing University of Posts and Telecommunications 2013
Area(s) of Expertise
Algorithms and Theory of Computation
Artificial Intelligence and Intelligent Agents
Cloud Computing
Cyber Security
Embedded and Real-Time Systems
Networking and Performance Evaluation
Parallel and Distributed Systems
Publications
- Traffic Engineering in Large-Scale Networks With Generalizable Graph Neural Networks , IEEE Transactions on Networking (2026)
- Wormholes in Space: Unveiling Wormhole Attack in Low Earth Orbit Satellite Networks , (2026)
- AdaOrb: Adapting In-Orbit Analytics Models for Location-aware Earth Observation Tasks , IEEE International Conference on Pervasive Computing and Communications (PerCom) (2025)
- Cost-Aware High-Fidelity Entanglement Distribution and Purification in the Quantum Internet , IEEE Transactions on Networking (2025)
- Mi-Co: Models and Algorithms for Cost-efficient Entanglement Distribution in the Quantum Internet , 2025 INTERNATIONAL CONFERENCE ON QUANTUM COMMUNICATIONS, NETWORKING, AND COMPUTING, QCNC (2025)
- Physics-Informed Mixed-Criticality Scheduling for F1Tenth Cars with Preemptable ROS 2 Executors , 2025 IEEE 31st Real-Time and Embedded Technology and Applications Symposium (RTAS) (2025)
- QuESat: Satellite-Assisted Quantum Internet for Global-Scale Entanglement Distribution , IEEE INFOCOM 2025-IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (2025)
- Rank-Based Modeling for Universal Packets Compression in Multi-Modal Communications , 2025 IEEE 26th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) (2025)
- Soteria: A Formal Digital-Twin-Enabled Framework for Safety-Assurance of Latency-Aware Cyber-Physical Systems , Proceedings of the 28th ACM International Conference on Hybrid Systems: Computation and Control (2025)
- FENDI: Toward High-Fidelity Entanglement Distribution in the Quantum Internet , IEEE/ACM Transactions on Networking (2024)
Grants
This proposal aims to develop techniques that enable application of robust predictive intelligence algorithms in the new spectrum era. The goal is to ensure robustness of predictive intelligence when handling critical spectrum-related tasks, including but not limited to: spectrum management, spectrum trading and spectrum monitoring.
This project aims to investigate the possibility and develop the technical foundation of building an open, decentralized wireless access ecosystem. The core contribution is around building contract overlay networks to enable on-demand spectrum leasing and wireless access, enabling verifiable contract fulfillment, and incentivizing broad and honest participation in the ecosystem.
This project seeks to develop theoretical tools (models and algorithms) for analyzing and optimizing a hybrid continuous-discrete variable quantum network architecture for the future quantum internet.
Abstract: The goal of this CAREER project is to fill the gap between growing application complexity and performance requirements, and existing application-agnostic network management, to enable and incentivize rigorous performance guarantees for distributed real-time applications at the network edge. The core contribution is the design, analysis, and evaluation of WolfPack, a general edge resource provisioning framework for real-time applications. The PI will focus on three key thrusts: 1) modeling and optimization of edge resource provisioning, 2) stochastic models and robustness techniques to control the risk, and 3) incentive mechanisms to enable truthful and competitive network edge resource trading.
Web applications play an important role in the current software ecosystem, and these web applications are usually built with certain supporting frameworks. While these frameworks ease the development of web applications, they bring several challenges to the analysis of web applications. Existing techniques analyze each request independently leading to suboptimal results. In this project, we propose inter-request analysis to go beyond the boundaries of individual requests, design a framework that can capture and express inter-request data and control dependencies, and develop several program analyses leveraging the framework for performance bug diagnosis, performance optimization, and flow integrity monitoring.
The potential of modern real-time applications, while enabled by advances in wireless communication technologies, is limited by the poor and unpredictable performance of the cloud backend as an Internet-based service. Edge computing is believed to be the magic bullet to this problem, but after years of research, we have yet witnessed the first large-scale deployment and utilization of edge computing. We believe the barrier is the lack of SLA-based performance guarantee, due to the inevitable risk of SLA violation. This project aims to take the first step in modeling and optimization of SLA violation risks in mobile edge computing.
Honors and Awards
- Goodnight Early Career Innovator Award, 2025-2026
- NSF CAREER Award, 2021