Rate My Professor William Eberle

William Eberle is a Professor of Computer Science in the Department of Computer Science at Tennessee Technological University, where he joined as Assistant Professor in 2007, was promoted to Associate Professor in 2012, and to full Professor in 2017. He serves as Assistant Dean of Graduate Education for the College of Engineering since September 2021 and as Co-Director of the Machine Intelligence and Data Science (MInDS) Center since August 2023. Previously, he held the Interim Assistant Dean of Academic Affairs position in the College of Engineering from 2017 to 2018. Before entering academia, Eberle worked in industry at General Dynamics, Lockheed Martin, and MCI (Verizon), designing, developing, and managing applications including flight simulators, decision support systems, marketing retention systems, war gaming, and fraud detection systems in telecommunications.

Eberle holds a Ph.D. in Computer Science (2007) from the University of Texas at Arlington, with a dissertation on information theoretic, probabilistic, and maximum partial substructure algorithms for discovering graph-based anomalies; an M.S. in Computer Science (1991) from the same institution; and a B.A. in Computer Science (1986) from the University of Texas at Austin. His research interests encompass data mining, graph theory, artificial intelligence, and software engineering, with specializations in graph-based anomaly detection applied to domains such as fraud in telecommunications and e-commerce, social networks, healthcare, financial transactions, insider threats, and security. He has received grants from the Department of Homeland Security and the National Science Foundation. Notable publications include 'Anomaly Detection in Dynamic Graphs: A Comprehensive Survey' (2024, with O.A. Ekle), 'Adaptive DecayRank: Real-Time Anomaly Detection in Dynamic Graphs with Bayesian PageRank Updates' (2025, with O.A. Ekle and J. Christopher), 'Scalable Anomaly Detection in Graphs' (2015, with L. Holder), and 'An Approach for Concept Drift Detection in a Graph Stream Using Discriminative Subgraphs' (2020, with R. Paudel). Eberle has earned the Douglas D. Dankel II Service Award from the Florida Artificial Intelligence Research Society (2023), Teacher-Scholar Awards from Tennessee Technological University (2013, 2014, 2016), Best Paper Award at FLAIRS (2009), and others. He chairs the Computer Science Personnel Committee and serves on the Graduate School Executive Committee, Computer Science Executive Committee, and numerous others, and has edited proceedings for FLAIRS conferences.