Cezary Z. Janikow

Cezary Z. Janikow is an Associate Professor and former Chair of the Department of Mathematics and Computer Science at the University of Missouri–St. Louis (UMSL), where he conducts research in artificial intelligence, evolutionary computation, and machine learning. He is the developer of FID (Fuzzy Inference Decision tree), a system for generating fuzzy decision trees that handle missing, noisy, and continuous data. His research is supported by NIH, NSF, and NASA/JSC, and he has contributed significantly to the field of genetic programming, particularly in constrained and adaptable representations (ACGP).

• Ph.D. in Computer Science, University of North Carolina at Chapel Hill, 1991

His research interests center on evolutionary algorithms, fuzzy decision trees, and symbolic machine learning. He explores how genetic programming can adapt representations and incorporate constraints to improve search efficiency and solution quality. His work on FID has advanced fuzzy logic applications in classification and data analysis.

The recent publications reflect a sustained focus on genetic programming, particularly Adaptable Constrained Genetic Programming (ACGP), heuristics in evolutionary search, and fuzzy decision systems. His work spans theoretical development, algorithm design, and practical implementation, with applications in optimization and machine learning.

Dr. Janikow has delivered corporate training in software development and served as an expert witness in software-related legal cases. He has also organized academic workshops and presented tutorials on evolutionary algorithms.

• Co-PI, NIH: Statistical Methods for Recursively Partitioned Trees
• NSF Support: Fuzzy Decision Trees
• NASA/JSC Collaboration: Constrained Genetic Programming

He leads the FID project, a software system for fuzzy decision tree generation, which includes a GUI and supports cross-validation and noise simulation. This tool reflects his integration of research and software development.