Sarah Lukens

Sarah is a fellow at LMI. She combines modern data science techniques with industry performance data to develop data-driven analytics for reliability applications. Using components from natural language processing, machine learning, and reliability engineering, Sarah analyzes asset maintenance data and creates statistical models to support asset performance management (APM) work processes. Sarah has 10 years of industry experience, developing industrial software solutions at Meridium and GE Digital prior to joining LMI.  

In 2010, she completed her PhD in mathematics from Tulane University with focus on scientific computing and numerical analysis. Sarah’s post-doctoral research at the University of Pittsburgh and the University of Notre Dame built data-driven computational models forecasting infectious disease spread and control. Sarah engages in the maintenance and reliability community through volunteer work with the Society of Maintenance and Reliability Professionals (SMRP) and the Prognostics and Health Management (PHM) Society. She is a Certified Maintenance and Reliability Professional (CMRP).