About me

Rhongho Jang is an assistant professor in the Department of Computer Science at Wayne State University. He received his Ph.D. in Computer Science from the University of Central Florida in 2020. He is the director of NIDS Lab.

Research: Programmable Switch, In-network Computing, Network Intelligence, Cyber Defense

Recent News

• [Mar 2026] Mehdi will join Google for his first summer internship!
• [Dec 2025] Low-and-slow threat detection paper accepted in USENIX NSDI 2026. Congrats to Mehdi!
• [Oct 2025] Mehdi is selected as a Distinguished AE Reviewer for USENIX Security, congrats!
• [Sep 2025] Malware concept drift paper to appear in Computing.
• [Apr 2025] Mehdi received Michael Conrad Award ($1,000) for USENIX Security 2024 paper, congrats!
• [Feb 2025] “SketchFeature” in-network defense paper to be presented at ISOC NDSS 2025.
• [Dec 2024] Best Paper Award at WISE 2024 for malware concept drift research.
• [Aug 2024] Mehdi’s first paper as lead author to be presented at USENIX Security 2024.
• [Aug 2023] Received NSF travel grant (PI) for IEEE CNS 2022.
• [Apr 2023] Hospital website security paper accepted in IEEE ICCCN 2023.
• [Feb 2023] In-network traffic measurement paper to be presented at ISOC NDSS 2023.
• [Sep 2022] Transformer explainability paper accepted in NeurIPS 2022.
• [Aug 2022] Received NSF HCC grant (Co-PI) for AI for social goods.
• [Jul 2022] In-network ACL defense paper to appear at ACM CCS 2022.
• [Jun 2022] Malware detection system analysis paper accepted in RAID 2022.
• [May 2022] Free content website analysis paper to be presented at ACM CySSS@AsiaCCS 2022.
• [Mar 2022] Flow spread estimation algorithm paper accepted in IEEE DSN 2022.
• [Aug 2021] DNS resolver behavioral analysis paper accepted in IEEE/ACM ToN.
• [Jul 2021] Robust malware detection paper accepted in IEEE TDSC.
• [Feb 2021] Wearable computing paper accepted in IEEE TMC.
• [Jan 2021] Best Fast Abstract Award for IoT malware defense at IEEE DSN 2021.
• [Jul 2020] Two papers (Security/Privacy) accepted in IEEE INFOCOM 2020.
• [Mar 2020] Malware adversarial learning paper accepted in IEEE ICDCS 2020.