About Me

I am an Assistant Professor in the Computer Science Department and the Electrical and Computer Engineering Department (by courtesy) at NCSU. Before joining NCSU, I received my PhD in Computer Science from Arizona State University in 2019, supervised by Dr. Guoliang Xue. I received my BS in Computer Science from Beijing University of Posts and Telecommunications in 2013. I was also a Research Assistant Intern at Tsinghua University from 2012 to 2013, supervised by Dr. Dan Li.

I am actively looking for self-motivated PhD students to conduct research on quantum networks, Internet-of-Things, edge computing, network security, machine learning, and the blockchain! If you are interested in my research below, please see my Students page for information on contacting me regarding research opportunities.

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Vision My research goal is to design and build high-performance, robust and usable systems for modern smart and connected communities, including smart homes, intelligent cities, and everything in between and beyond. Challenges exist in dimensions including scale, heterogeneity, reliability, security and usability, and my research focuses on developing techniques against them stemming from the Internet-of-Things, cloud and edge computing, wireless and mobile networks, security and privacy, data analytics and machine learning, network economics, the blockchain, and quantum networks. The complexity of modern intelligent systems is enormous, but because of this the possibilities for research are infinite!

Methodology Typical Computer Science research (in most areas) divides into two categories: systems and theory. Systems research focuses on building actual systems or components of a system in seek for practical enhancement over the state-of-the-arts, while theoretical research is meant to abstract systems with mathematical modeling to reflect, generalize, optimize, and explore the limits of, what an actual system can achieve. Since both are eventually to serve the applications, i.e., what can benefit our world in the end, I am interested in pursuing, not the divided efforts in either, but the combined research of both theory and systems, for the joint good of both. I call it Research on Integrated Theory And Systems (RITAS).

Toolset My research toolset has been developed around the core of RITAS. On the theory side, I am proficient with modeling, optimization, and algorithm design. These include (but are not limited to) linear programming, mixed integer programming, (non-)convex optimization, network flow, approximation algorithms and schemes, and robust design and optimization. On the system side, I am comfortable interacting with network devices (switches, routers, APs), IoT platforms (Raspberry Pi), real-world network simulators/emulators (NS-3, Mininet), and blockchains (Bitcoin, Ethereum), besides numerous other networked systems and applications. My toolset is never static and constantly growing, with new candidates including statistical modeling and optimization, blackbox optimization, deep reinforcement learning, crypto analysis and provable security, and risk management. If your research requires any of these tools and you see potential collaborations, shoot me an email and I will respond the soonest I can.


PhD in Computer Science, Arizona State University, 2019

BS in Computer Science, Beijing University of Posts and Telecommunications, 2013


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