Jami J. Shah

Jami J. Shah's research focuses on computer-aided engineering design and manufacturing, including design for manufacturability (DFM), CAD data representation, and increasingly the use of machine learning to predict manufacturing outcomes and support design decisions. Recent work applies data-driven and machine-learning methods to problems like stamping automotive parts, predicting material springback, and curating large engineering datasets for training design algorithms. The work bridges traditional mechanical/manufacturing engineering with modern data science techniques.

Publication output has gradually declined from about 5-7 papers per year in 2017-2019 to roughly 1-4 papers per year in recent years, though there has been a slight uptick since 2023.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026