Summary
Shengyen Li is a mechanical engineer with 11 years of experience applying data-enabled approaches, materials informatics, and computational modeling to solve quality, reliability, and design challenges in additive manufacturing and materials discovery. Currently at NIST he develops digital twins for AM processes that integrate statistical analysis and physics-based models to inform part and process design, building on prior work creating hierarchical modeling and informatics systems at Southwest Research Institute. He has deep experience bridging data, simulation, and decision-makers—contributing to ASTM F42 data model efforts and presenting AM reliability work at ADETC-CIE 2024. Trained as a PhD materials scientist from Texas A&M, Shengyen blends rigorous research with practical engineering to turn complex datasets into actionable, auditable solutions.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Materials Science, Doctor of Philosophy - PhD, Materials Science at Texas A&M University