Thursday, 12 Mar
10:15-11:00
Chris Gotwalt leads the statistical software development and testing teams for JMP Statistical Discovery. His passion is developing new technologies that accelerate innovation in industry and science. Since joining the company as a Ph.D. student intern in 2001, Gotwalt has contributed many numerical algorithms and new statistical techniques. He has authored many algorithms in JMP, including those for fitting linear mixed models and optimal design of experiments.
Presentations
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Applying DOE to Large Language Models (2026-EU-30MP-2761)
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Bayesian Optimization for Formulations Involving Complex Constraints with JMP 19 (2026-EU-30MP-2816)
Wednesday, 11 Mar
10:45-11:30
- High Impact JMP Pro 19 Capabilities
- JMP R&D Lightning Talks Plenary
- Design Space Profiler Plenary
- JMP R&D Lightning Talks Plenary
- Exploiting JMP Pro to Model Outlier Distributions in Semiconductor Process Development (2024-EU-PO-1662) Plenary
- Choosing Models in JMP with Model Selection Criteria - (2023-US-30MP-1456) Plenary
- 寻找黄金曲线：实现函数响应DOE分析 Plenary
- Candidate Set Designs: Tailoring DOE Constraints to the Problem (2021-EU-30MP-784) Plenary
- Introduction to Functional Data Analysis (2019-US-TUT-289) Plenary
- Introduction to Functional Data Analysis ( 2019-EU-TUT-140 ) Plenary
- Introduction to Machine Learning With JMP® Pro ( 2019-EU-TUT-141 ) Plenary
- Model Validation Strategies for Designed Experiments Using Bootstrapping Techniques With Applications to Biopharmaceuticals ( US 2018 218 ) Plenary
- Plenary - Christopher Gotwalt - Functional Data Explorer Plenary
- Tutorial - Using Functional Data Explorer to Make Sense of Sensor Data (US 2018 410) Plenary
- Visually Exploring Design of Experiments Models With the Generalized Regression Platform Plenary