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Knowledge Discovery and Data Mining focuses on the process of extracting meaningful patterns from biomedical data (knowledge discovery), using automated computational and statistical tools and techniques on large datasets (data mining). Its underlying goal is to help humans make high-level sense of large volumes of low-level data, and share that knowledge with colleagues in related fields. It can involve methods for data preparation, cleaning, and selection, use of appropriate prior knowledge, development and application of data mining algorithms, and proper results analysis. It engages methods from such diverse areas as machine learning, pattern recognition, database science, statistics and analytics, artificial intelligence, knowledge acquisition for expert systems, data modeling and visualization, and high performance computing.

Leadership

Profile image for Lixia Yao, PhD

Lixia Yao, PhD

Chair 2021-2022
Director, Real-world Data Analytics & Innovation
Merck
Profile image for Ying Li

Ying Li

Chair Elect 2022
Regeneron Pharmaceuticals
Profile image for Zhe He, PhD, FAMIA

Zhe He, PhD, FAMIA

Secretary 2020-2022
Associate Professor & Informatics Lead
Florida State University