The Engineering Statistics and Machine Learning Laboratory (ESAMLab), was founded in 2000 by Dr. Enrique del Castillo, Professor of Industrial Engineering and Professor of Statistics at Penn State. The ESAMLab’s mission is to conduct advanced research in statistical and machine learning methodologies across the spectrum of engineering disciplines and experimental sciences. Since its inception in 2000 as the Engineering Statistics Lab, work at the ESAMLab focuses on how to build “big-data”-based statistical models for the control and optimization of engineering systems or that provide helpful information to scientists. Recent work focuses on processes that generate (either through observation or experimentation) large heterogeneous datasets, specifically, data that occur along one dimensional “profiles” (functional data), data that occur in a 2D space, and data in a higher-dimensional manifold (e.g., 3D point cloud of surfaces and image data). Examples of these types of data in manufacturing are shape and metrology data. Usually, the control and optimization problems we address require new methodology for experimental design, model fitting and statistical inference, resulting in contributions at the intersection of Statistical Sciences and Machine Learning.
- Semiconductor Manufacturing
- Advanced Machining processes, including 3D printing
- Metrology and statistical image modeling and inference
- Pharmaceutical drug development analysis
- Automobile Design
- Network modeling