Rate My Professor Pamela Thompson

Pamela Thompson, Ph.D., serves as Associate Professor of Information Systems in the Department of Mathematical and Computing Sciences at Catawba College, part of the Ralph W. Ketner School of Business. She earned her 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. Her professional activities encompass systems consulting and systems design, with academic interests centered on applications development and web design. Dr. Thompson's expertise includes 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, beacons, near field communication, programming, social media, and women in business.

In her career at Catawba College, Dr. Thompson has held key appointments, including Interim Chair of the Ketner School of Business. She advises the Tech Club and serves as faculty advisor for FBLA-Collegiate, where her students have earned national recognition at conferences such as the FBLA-C National Leadership Conference. As an adjunct lecturer in the School of Data Science and College of Computing and Informatics at UNC Charlotte, she contributes to graduate faculty and teaches courses like Big Data Design, Storage, and Provenance in Healthcare. Dr. Thompson's research specializes in data science applications, including mining proprietary big data from acoustic telemetry to predict great white shark presence in nearshore waters off Cape Cod. This interdisciplinary work integrates weather data and machine learning for predictive modeling. Her Ph.D. dissertation focused on mining knowledge to build a decision support system for tinnitus diagnosis and treatment. She presented 'Developing a Recommender System for Shark Presence along East Coast Beaches' at the SAS Deep Learning Symposium, selected from 55 applicants, and co-presented 'Bridging Trust and Technology: Explainable AI in Action' at the 2025 Charlotte Women in Data Science Conference, utilizing techniques such as SHAP, PDP, ALE, LIME, and rule-based interpretations on shark movement data.