Wajih Ul Hassan

Wajih Ul Hassan is an Assistant Professor of Computer Science at the University of Virginia (UVA), affiliated with the School of Data Science. He leads the DART Lab, focusing on system intrusion detection, forensic investigation, and cybersecurity through machine learning and data provenance techniques. His research has earned prestigious awards including the NSF CAREER Award (2024) and Symantec Research Labs Graduate Fellowship.

Dr. Hassan holds a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign (2021). He has collaborated with NEC Labs and Symantec Research Labs to integrate defensive strategies into commercial security products. His work emphasizes practical solutions for networked systems and scalable security mechanisms.

He teaches courses such as CS 6501: Machine Learning in Systems Security, CS 4630: Defense Against the Dark Arts, and DS 6559: Machine Learning in Systems and Network Security. His research interests span intrusion detection, provenance analytics, and automated threat response, with over 20 peer-reviewed publications since 2017.

Award Highlights:

• NSF CAREER Award (2024)
• ACM SIGSOFT Distinguished Paper Award
• Young Researcher at Heidelberg Laureate Forum

Service Activities: He has served on program committees for top-tier conferences (e.g., IEEE S&P, ACM CCS) since 2018 and reviewed grants for the NSF and Commonwealth Cyber Initiative.

Labs & Teams: The DART Lab at UVA focuses on advancing enterprise security through data-driven approaches. Dr. Hassan actively recruits students for research projects in cybersecurity and systems security.