Gotwalt leads the statistical software development and testing team for JMP Statistical Discovery. His passion is developing new technologies that accelerate innovation in industry and science. Since joining the company as a PhD student intern in 2001, Gotwalt has contributed to many numerical algorithms and new statistical techniques. In JMP, he developed neural networks, linear mixed models, optimal experimental designs, analytical procedures for text analytics, and fitting algorithms for structural equation models. Gottwalt is the principal investigator of Self-Validating Ensemble Models (SVEM), a procedure that enables machine learning for small data sets frequently encountered in industry. He has served as an adjunct lecturer at North Carolina State University, the University of Nebraska, and the University of New Hampshire, and was the 2020 Chair of the American Statistical Association's Division on Quality and Productivity.
