William Eberle

William Eberle is a Professor of Computer Science and Interim Assistant Dean of Graduate Education at the College of Engineering, Tennessee Technological University. He holds a Ph.D. and M.S. in Computer Science from the University of Texas at Arlington and a B.A. in Computer Science from the University of Texas at Austin. His research focuses on graph-based anomaly detection, fraud detection, data mining, and artificial intelligence, with applications in telecommunication, healthcare, and cybersecurity. He has led industry projects in fraud detection systems and currently explores scalable anomaly detection in dynamic graphs. Dr. Eberle teaches courses in data science, software engineering, and anomaly detection. He advises numerous graduate students and has contributed to funded research through the Department of Homeland Security and National Science Foundation.

Education:

• Ph.D. in Computer Science, University of Texas at Arlington (2007)
• M.S. in Computer Science, University of Texas at Arlington (1991)
• B.A. in Computer Science, University of Texas at Austin (1986)

Research Interests:

• Graph-Based Anomaly Detection (GBAD)
• Scalable algorithms for dynamic graph streams
• Fraud Detection in telecommunications, finance, and healthcare
• Explainable AI and ethical automated decisions

Notable Projects:

• Developed PLADS software for pattern learning and anomaly detection in streams
• NSF-funded research on anomaly detection in graph streams
• DOE-funded work on insider threat detection systems

Teaching:

• Graduate courses: Data Mining, Anomaly Detection Systems
• Undergraduate courses: Software Engineering, Data Science, AI

Labs/Teams: Active contributor to Tennessee Tech’s data science and cybersecurity initiatives, collaborating with industry partners on fraud detection and network security solutions.