Machine Learning & Safety Analytics Lab

I established MLSA Lab in the Technology Department in Spring 2019 to conduct research on various applications of machine learning and predictive analytics in industrial systems. My research interests lie in applied machine learning and predictive modeling of industrial systems, quality management and lean manufacturing, and statistical modeling of industrial occupational incidents for improving safety outcomes.

My spesific research interests are:

  • Safety analytics in occupational incidents
  • Applied machine learning for prognostics and health management in manufacturing systems
  • Theory-guided data science for industrial systems modeling and optimization
  • Geometric machine learning for reliability assessment of cyber-physical systems in manufacturing 

If you are a BS/MS student interested in pursuing a thesis, project, or looking for research experience in applications of machine learning and deep learning in manufacturing optimzation, lean manufacturing and six sigma, or statistical modeling of industrial systems, please email your CV to


Projects (since 2018):

  1. Deep Learning for Process Monitoring in Semiconductor Manufacturing (Co-PI; $163,000 funded for 9/01/2022 to 12/31/2023)
  2. Evaluation Plan Development for DMV (Co-PI; $50,000 funded for 12/20/2021 to 5/31/2022)
  3. Machine Learning in Autonomous Systems (Co-PI; $100,000 funded for 1/1/2020 to 5/31/2022)
  4. Machine Learning for Quality Improvement in Industrial Operations (PI; $180,000 funded for 8/01/2020 to 6/31/2022)
  5. Machine Learning for PID Controller Optimization (PI; $100,000 funded for 8/01/2020 to 6/31/2022)
  6. Hybrid Machine Learning Models for Transportation Safety Enhancement (PI; $75,000 funded for 5/15/2020 to 7/31/2021)
  7. Safety Analytics in Occupational Incidents (Collaboration with Dr. Steve Freeman and Dr. Gretchen Mosher, Iowa State University)