Sarah Gilyard is a Senior Product Manager for JMP Statistical Discovery, where she leads initiatives in advanced analytics for JMP Pro. Her main areas of focus include predictive modeling, clustering, the Bayesian Optimization platform, multivariate and mixed model platforms, and Functional Data Explorer. Gilyard also plays a critical role in shaping JMP’s software development strategy, with a particular emphasis on addressing the complex analytical needs of the semiconductor industry.
After studying mathematics and statistics in graduate school, she began her career providing statistical consulting support to fab engineers and other semiconductor professionals – specializing in the areas of experiment design, predictive modeling, visualization, and data mining.
Before joining JMP, Gilyard spent 16 years in the semiconductor industry, holding various roles in fab processing and equipment engineering.
Presentations
- From rules to generators: A survey of intelligent tools in JMP
- Opening Address / Scaling Innovation: Integrating Data Science into Engineering Workflows
- 開会のご挨拶／基調講演：イノベーションの拡大：エンジニアリング・ワークフローへのデータサイエンス統合
- Bayesian Optimization: A Goal-Oriented Approach for Process Development (2025-US-30MP-2554)
- JMP Product Roadmap and Developer Lightning Talks
- Scaling Innovation: Integrating Data Science into Engineering Workflows Plenary