Carlos a EscobarCarlos Alberto Escobar Diaz is a machine learning engineer ranked in the top 3% in TEXATA, the Big Data Analytics World Championships. He holds a Ph.D. in Engineering Sciences with concentration in Artificial Intelligence (AI) and a master's degree i Quality Engineering from Tecnológico de Monterrey and a master's in Industrial Engineering from New Mexico State University. Currently he is pursuing a master's in Management at Harvard Extension School. He also holds black belt in six sigma and design for six sigma (DFSS) certifications from Arizona State University and University of Michigan respectively, DFSS master black belt from General Motors, and an Artificial Intelligence: Implications for Business Strategy certification from Massachusetts Institute of Technology. He is a member of Alpha Pi Mu and Tau Beta Pi engineering honor societies. Escobar is a Senior Researcher at the Manufacturing Systems Research Lab of General Motors, Global Research and Development. His research interests include the application of AI techniques to solve a full range of hitherto intractable manufacturing problems, especially in the domain of rare quality event detection. His research work in Quality 4.0 is supported by more than 25 peer-reviewed scientific articles and it has been recognized as one of the innovative and high impact research topics by the TecReview Magazine. Read More Read Less