Nathan Haut

Nathan Haut is a Fixed Term Assistant Professor in the Department of Computational Mathematics, Science and Engineering at Michigan State University. His research focuses on symbolic regression, genetic programming, and active learning techniques for optimizing computational models.

• Academic Rank: Assistant Professor
• Department: Computational Mathematics, Science and Engineering
• Email: hautnath@msu.edu

Haut's work explores model complexity assessment, sharpness-aware minimization, and multi-objective optimization in genetic programming. He applies these methods to biomedical data analysis, quantum systems, and environmental modeling, emphasizing algorithm efficiency and robustness.

Recent publications highlight his contributions to symbolic regression tasks using active learning strategies, differential equations for tile drainage modeling, and benchmarking loss functions like correlation versus RMSE. His research bridges theoretical advancements with practical applications in computational mathematics.