Charles Nicholas

Charles Nicholas is a Professor of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a Ph.D. in Computer and Information Science from Ohio State University (1988), an M.S. from the same institution (1982), and a B.S. in Computer Science from the University of Michigan–Flint (1979). His research focuses on applying data science and machine learning to cybersecurity challenges, particularly in ransomware analysis, malware detection, and threat intelligence. He previously served as Chair of UMBC’s Department of Computer Science and Electrical Engineering (2004–2010) and has chaired the Conference on Information and Knowledge Management five times.

His work spans cutting-edge topics such as quantum algorithms for malware classification, knowledge graph generation, and efficient feature extraction methods for malware detection. Notable contributions include frameworks for evaluating malware datasets, improving classifier robustness, and leveraging antivirus scan data for large-scale analysis.

Dr. Nicholas is a Senior Member of both ACM and IEEE, reflecting his longstanding contributions to the field. His research emphasizes practical applications of machine learning to cybersecurity, with a focus on scalable solutions for real-world threats.