Pang-Ning Tan

Dr. Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University (MSU), part of the College of Engineering. His research focuses on data mining and machine learning, with applications in climate science, cybersecurity, network analysis, and medical informatics. He holds a Ph.D. in Computer Science and an M.S. in Physics from the University of Minnesota.

Education:

• Ph.D., Computer Science, University of Minnesota (2002)
• M.S., Physics, University of Minnesota (1996)

Research Interests: Dr. Tan’s work spans fundamental data mining techniques and their real-world applications. Key areas include pattern discovery, predictive modeling, extreme event forecasting, and fairness-aware machine learning. His research has been funded by the National Science Foundation, NASA, and other agencies. Recent projects involve climate modeling, social network analysis, and health informatics.

Grants & Collaborations: Active funding sources include NSF, ONR, and NASA. Collaborations span interdisciplinary teams in ecology, climate science, and healthcare. He co-authored the textbook Introduction to Data Mining (2nd Ed., Addison-Wesley), a widely adopted resource in data science education.

Software & Tools: Developed tools like PGMiner (closed frequent itemset mining) and contributed to frameworks for hurricane trajectory forecasting (JOHAN), drought analysis (Automated Analysis of US Drought Monitor Maps), and extreme event modeling (DeepExtrema).

Students & Advising: Advised over 20 graduate students, with recent alumni in academia and industry. Current advisees include Asadullah Galib and Francisco Santos.