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About Pamela
Pamela Thompson, Ph.D., is Associate Professor of Information Systems in the Department of Mathematical & Computing Sciences at Catawba College, part of the Ralph W. Ketner School of Business. She holds a Ph.D. in Information Systems from the University of North Carolina at Charlotte, an M.B.A. from James Madison University, and a B.B.A. in Management Information Systems from James Madison University. A faculty member at Catawba since 1991, Thompson has advanced through significant administrative roles, serving as interim chair of the Ketner School of Business during the spring 2006 semester and as Dean of the school until August 1, 2015, when she returned to full-time teaching duties in Ketner Hall. Her professional activities encompass systems consulting and systems design.
Thompson's academic interests center on applications development and web design, with recognized expertise in app development and coding, computer science, data mining, machine learning, knowledge discovery with databases, data analytics, data integration, e-commerce, technology entrepreneurship, information systems, Internet of Things including beacons and near field communication, programming, social media, and women in business, as listed on Catawba College's experts directory. She has contributed to scholarly work, co-authoring publications such as 'Mining Tinnitus Data Based on Clustering and New Temporal Features' in 2012 and 'Initial Analysis of Multivariate Factors for Prediction of Shark Presence' in 2018, affiliated with both UNC Charlotte and Catawba College. As faculty advisor for Future Business Leaders of America - Phi Beta Lambda, she accompanied Catawba students to the 2017 national conference, where they earned awards, and judged competitive events. In March 2025, Thompson co-presented 'Bridging Trust and Technology: Explainable AI in Action' at the Charlotte Women in Data Science Conference, demonstrating techniques like SHAP and LIME on shark telemetry data. She also serves as adjunct faculty in UNC Charlotte's School of Data Science.