معرفی
Wajih Ul Hassan is an Assistant Professor of Computer Science at the University of Virginia (UVA), leading the DART Lab. His research focuses on system security, emphasizing practical solutions for safeguarding networked systems using data-driven approaches and scalable design. He was awarded the NSF CAREER Award in 2024. His service roles include program committee (PC) membership at IEEE S&P, NDSS, ACM CCS, and NSF panel participation since 2018.
Research Interests: Hassan’s work centers on intrusion detection, provenance analytics, threat detection, and forensic analysis. He explores how provenance graphs and machine learning can enhance cybersecurity resilience against advanced persistent threats (APTs), AR/VR attacks, and configuration-based exploits.
Teaching: He teaches CS 6501: Machine Learning in Systems Security, CS 4630: Defense Against the Dark Arts, and DS 6559: Machine Learning in Systems and Network Security. Courses emphasize threat detection, vulnerability management, and forensic investigation.
Awards:
- NSF CAREER Award (2024)
Labs & Teams: Directs the DART Lab, focused on applied security research and scalable defense mechanisms.
