Carlos A. Escobar, PhD

Machine learning research scientist

Research Expertise

Applied and develop machine learning algorithms to solve engineering intractable problems
Industrial and Manufacturing Engineering
Modeling and Simulation
Mechanical Engineering
Artificial Intelligence
Software
Control and Systems Engineering
Computer Science Applications
Mechanics of Materials
Safety, Risk, Reliability and Quality
Health Informatics
Health Policy
Information Systems and Management
Cultural Studies
Literature and Literary Theory
History

About

Carlos obtained his PhD in Engineering Sciences with concentration in AI/ML from Tec de Monterrey. He worked as a Research Assistant at Harvard. Research Scientist at Amazon, Last Mile Delivery Technology Team, where he developed and applied algorithms to speed up customer delivery times and provide new innovations to customers. Before joining Amazon, Carlos worked for General Motors (GM) as a Senior Researcher at the Manufacturing Systems Research Lab. He conducted research in Industry 4.0 and Quality 4.0; applied and developed algorithms to drive manufacturing innovation. <br> Carlos is the author of the book “Machine Learning in Manufacturing: Quality 4.0 and the Zero Defects Vision”. His research work interest lies within the 99% percentile as compared with the cohort of researchers registered in the ResearchGate platform and it has been recognized as one of the most innovative and high impact research topics by the TecReview magazine. He was ranked in the top 3% in TEXATA, the Big Data Analytics World Championships. Carlos was recognized as the SHPE Star of Today by the Society of Hispanic Professional Engineers (SHPE). This award honors an engineer/scientist who has demonstrated outstanding technical excellence resulting in significant accomplishments. It also recognizes dedication, commitment, and selfless efforts to advance Hispanics in STEM careers. Carlos was in the Mexican national team of martial arts. Today he enjoys teaching his colleagues this sport. SHPE: https://www.shpe.org/events/nc2021/programs/star-awards TecReview: https://issuu.com/tecreview/docs/tec\_review-30 ResearchGate profile: https://www.researchgate.net/profile/Carlos\_Escobar31 Google Scholar: https://scholar.google.com/citations?user=3JfYEaUAAAAJ&hl=en

Legacy Map

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Publications

Educational experiences with Generation Z
International Journal on Interactive Design and Manufacturing (IJIDeM)
2020
Competencies for Industry 4.0
International Journal on Interactive Design and Manufacturing (IJIDeM)
2020
Machine learning techniques for quality control in high conformance manufacturing environment
Advances in Mechanical Engineering
2018
Engineering education for smart 4.0 technology: a review
International Journal on Interactive Design and Manufacturing (IJIDeM)
2020
Technologies for the future of learning: state of the art
International Journal on Interactive Design and Manufacturing (IJIDeM)
2019
Quality 4.0: a review of big data challenges in manufacturing
Journal of Intelligent Manufacturing
2021
Big Data-Driven Manufacturing—Process-Monitoring-for-Quality Philosophy
Journal of Manufacturing Science and Engineering
2017
Learning analytics: state of the art
International Journal on Interactive Design and Manufacturing (IJIDeM)
2022
Biometric applications in education
International Journal on Interactive Design and Manufacturing (IJIDeM)
2021
Machine Learning and Pattern Recognition Techniques for Information Extraction to Improve Production Control and Design Decisions
Advances in Data Mining. Applications and Theoretical Aspects
2017
Process-Monitoring-for-Quality — Big Models
Procedia Manufacturing
2018
Quality 4.0 — Green, Black and Master Black Belt Curricula
Procedia Manufacturing
2021
Process-Monitoring-for-Quality—Applications
Manufacturing Letters
2018
Quality 4.0 – an evolution of Six Sigma DMAIC
International Journal of Lean Six Sigma
2022
Process-Monitoring-for-Quality — A Model Selection Criterion for l - Regularized Logistic Regression
Procedia Manufacturing
2019
Process-Monitoring-for-Quality — A Model Selection Criterion for Support Vector Machine
Procedia Manufacturing
2019
Process-monitoring-for-quality — A model selection criterion
Manufacturing Letters
2018
The decay of Six Sigma and the rise of Quality 4.0 in manufacturing innovation
Quality Engineering
2023
Process-monitoring-for-quality — A machine learning-based modeling for rare event detection
Array
2020
Process-Monitoring-for-Quality - A Step Forward in the Zero Defects Vision
SAE Technical Paper Series
2020
Process monitoring for quality — A multiple classifier system for highly unbalanced data
Heliyon
2021
Process-Monitoring-for-Quality—A Model Selection Criterion for Genetic Programming
Lecture Notes in Computer Science
2019
Prognosis patients with COVID-19 using deep learning
BMC Medical Informatics and Decision Making
2022
Interpreting learning models in manufacturing processes: Towards explainable AI methods to improve trust in classifier predictions
Journal of Industrial Information Integration
2023
Process-Monitoring-for- Quality — A Model Selection Criterion for Shallow Neural Networks
Annual Conference of the PHM Society
2019
Learning with Missing Data
2020 IEEE International Conference on Big Data (Big Data)
2020
Process-monitoring-for-quality—A robust model selection criterion for the logistic regression algorithm
Manufacturing Letters
2019
Discrete Event Simulation
Simulation‐Based Lean Six‐Sigma and Design for Six‐Sigma
2006
Augmentation of Body-in-White Dimensional Quality Systems through Artificial Intelligence
2021 IEEE International Conference on Big Data (Big Data)
2021
Process monitoring for quality–a feature selection method for highly unbalanced binary data
International Journal on Interactive Design and Manufacturing (IJIDeM)
2022
Correction to: Process monitoring for quality - a feature selection method for highly unbalanced binary data
International Journal on Interactive Design and Manufacturing (IJIDeM)
2022

Education

Harvard University

Masters, Management / August, 2024 (anticipated)

Cambridge, Massachusetts, United States of America

Monterrey Institute of Technology and Higher Education

PhD, Engineering Sciences / 2019

Monterrey

New Mexico State University

Masters

Las Cruces, New Mexico, United States of America

Monterrey Institute of Technology and Higher Education

Masters, Quality and Systems Engineering / 2005

Monterrey

Experience

Harvard

Amazon

General Motors

Links & Social Media

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