Mingming Chen

Mingming Chen

Assistant Professor at Kansas State University

Biography

I am an assistant professor in Computer Science at Kansas State University. I recently earned my Ph.D. in Computer Science and Engineering from Penn State University. I was honored to be advised by Tom La Porta and Trent Jaeger. I am also grateful for the IBM Research collaboration and guidance from Teryl Taylor and Fred Araujo. My research focuses on the security and trustworthiness of programmable and distributed networked systems, with a particular emphasis on Software-Defined Networking (SDN) control planes. Using SDN as a concrete systems substrate, I study how control planes construct global views, make decisions, and can be misled or protected under adversarial manipulation—uncovering architectural vulnerabilities and developing defenses that make system perception and actuation trustworthy by construction. Building on this foundation, I am exploring security challenges in emerging AI-driven infrastructures, such as GPU cluster communication and RDMA-based systems, where new cross-layer vulnerabilities and trust assumptions arise. My work has appeared in ACM CCS and USENIX Security and has led to the disclosure of multiple CVEs affecting widely used SDN controllers. I have hands-on experience with open-source SDN platforms, having contributed code to OpenDaylight earlier in my career. I also serve on program committees and artifact evaluation boards in the security community.

Upcoming: I will join the Department of Computer Science at the University of Texas at Dallas as an Assistant Professor in August 2026.

Prospective Students

I am always looking for motivated students interested in the security and trustworthiness of programmable and distributed networked systems. My current research interests include:

  • Security & Privacy of next-G Network Slicing: Study topology abstraction as a foundational security and privacy interface in network slicing, where incorrect or overly revealing abstractions can lead to SLA violations, isolation failures, and information leakage.
  • Secure and Trustworthy SDN Control Planes: Studying information-flow-based security analysis of SDN control planes to uncover architectural misuse cases in network discovery, state maintenance, and controller–data-plane interactions, and designing secure-by-construction control-plane mechanisms.
  • AI Infrastructure Network Security: Study security challenges in large-scale AI infrastructures, including accelerator communication and multi-tenant interference. Design mechanisms for isolation, robustness, and trustworthy operation.

How to apply: Please email your CV, transcript, and a brief research statement. Email subject: Prospective PhD application.

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