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Ruozhou Yu

RY

Assistant Professor

2403 Engineering Building III (EB3)

919-515-7938 Website

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

View all publications

Grants

Date: 10/01/24 - 9/30/27
Amount: $400,000.00
Funding Agencies: National Science Foundation (NSF)

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.

Date: 10/01/24 - 9/30/27
Amount: $305,746.00
Funding Agencies: National Science Foundation (NSF)

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.

Date: 09/01/24 - 8/31/27
Amount: $300,000.00
Funding Agencies: National Science Foundation (NSF)

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.

Date: 07/01/21 - 6/30/26
Amount: $521,722.00
Funding Agencies: National Science Foundation (NSF)

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.

Date: 08/15/20 - 7/31/24
Amount: $350,000.00
Funding Agencies: National Science Foundation (NSF)

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.

Date: 10/01/20 - 9/30/23
Amount: $142,500.00
Funding Agencies: National Science Foundation (NSF)

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.


View all grants
  • Goodnight Early Career Innovator Award, 2025-2026
  • NSF CAREER Award, 2021