Summary
Kevin Cruse is a machine learning scientist with 8 years of experience applying data-driven methods to unravel materials synthesis science, currently focusing on LLM-backed knowledge extraction and lab orchestration at Lila Sciences. He has a strong track record building and managing TB-scale literature databases, transforming unstructured text via robust data pipelines, and training predictive models to reveal synthesis–property relationships. His work spans academia and industry—from Berkeley Lab postdoc projects mining millions of articles to productionizing fine-tuned large language models for experimental design and patent analysis. Kevin combines a PhD in Materials Science with hands-on software and data engineering skills, enabling seamless translation of research models into deployed systems. Outside of work he brings creative discipline from a dual background in jazz performance and engineering, regularly gigging as a drummer while cooking and hiking with his fiancé. His GitHub and publications reflect a rare blend of text mining, web scraping, and materials informatics expertise aimed at accelerating materials discovery.
8 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD Materials Science, Doctor of Philosophy - PhD Materials Science at University of California, Berkeley
Bachelor of Science (B.S.) Mechanical Engineering, Bachelor of Science (B.S.) Mechanical Engineering at University of Illinois Urbana-Champaign