Exploring Psychology, Social Innovation and Advanced Applications of Machine Learning

Machine learning (ML algorithms can be used to better understand human behavior in its various developmental stages and to assist in addressing psychological issues. Additionally, in the realm of mental health and well-being, algorithms can assist with early detection of disorders and customization of treatments as well as personalize recommendations and suggestions based on user behavior. By focusing on user experience and usability, ML may be used to address challenges faced by private enterprises and social issues. Exploring Psychology, Social Innovation and Advanced Applications of Machine Learning explores the relationships between human psychology and machine learning technology, enabling researchers to delve into areas such as user interface design, ethics in artificial intelligence, and the social impact of algorithms. Furthermore, it promotes interdisciplinary collaboration by bringing together perspectives from different fields, which could stimulate new research and innovative approaches in the field of machine learning. Covering topics such as industrial processes, digital therapy, and machine vision, this book is an excellent resource for psychologists, computer scientists, engineers, healthcare practitioners, educators, business leaders, policymakers, professionals, researchers, scholars, academicians, and more.

María E. Raygoza-L. has a PhD in Chemistry and Energy from the Engineering Institute of the Universidad Autónoma de Baja California and a bachelor’s degree in industrial engineering with a specialization in Manufacturing. The thesis topic developed was “Technological Management for the transfer of Renewable Energies”, carrying out an academic stay at the Colegio de la Frontera Norte where she investigated public policies for the energy transition and sustainable development of Mexico, achieving a methodology that aims the integration of the main actors that must contribute to sustainable development. She currently works as a full-time professor and researcher at the Universidad Politécnica de Baja California and as a subject professor at the Universidad Autónoma de Baja California, with a specialty in Energy Engineering and Renewable Energies, contributing to the training of quality human resources. With extensive experience in the food and aerospace industries, his research interests span renewable energy, energy efficiency, environmental studies, energy management systems, and the integration of public policies for sustainable development and transition through social energy innovation and emerging technology applications such as Artificial Intelligence, especially Machine Learning. He is currently pursuing a Second bachelor’s degree in psychology, further expanding his academic horizons in relation to social applications of public policies and social innovation that have an impact on sustainable development, addressing issues of energy security, sustainability, renewable energy and water stress, focusing their research to the fulfillment of the Sustainable Development Goals (SDGs).

Jesus Orduño received his B.Sc. in Mechatronics Engineering from the Universidad Politécnica de Baja California (UPBC) in 2020 and his M.Sc. in Computational Sciences and Applied Mathematics from Universidad Internacional de La Rioja, Mexico (UNIR Mexico) in 2024. His professional experience spans the Post-Harvest Automation and manufacturing sectors, where he has specialized in automation processes, vision systems, and industrial robotics. Currently, he works as a part-time lecturer at Universidad Politécnica de Baja California, where he teaches courses related to Mechatronics, Manufacturing, Energy Systems, and Computer Science. His teaching is complemented by his active research interests in Machine Learning, Automation and Control of Industrial Processes, Microcontrollers, and Digital Signal Processing (DSP), areas in which he seeks to advance the integration of intelligent systems in industrial applications.

Abelardo Mercado-Herrera is a Doctor of Science and Master of Science from the National Institute of Astrophysics, Optics and Electronics, specializing in Astrophysics, Postdoctorate in Astrophysics from the Institute of Astronomy of the National Autonomous University of Mexico, Electronics Engineer from the Autonomous University of Baja California . He is a specialist in the mathematical-statistical description of stochastic and/or deterministic processes, nonlinear systems, complex systems, chaos theory, among others, as well as their application to physical phenomena such as astronomy, economics, finance, telecommunications, science social etc., in order to determine the underlying dynamics in such processes, and if necessary, their connection with real physical variables and possible prediction. He has worked on the development of various electronic circuits, interfaces and programs to carry out electrical tests in the industry, as well as in scientific instrumentation, applied to telemetry, infrared polarimetry, optics and spectroscopy. He has also specialized in image analysis, measurement techniques and noise reduction.

Roxana Jimenez-Sanchez is a Doctoral candidate in International Industrial Safety at Applied Pedagogical University, Monterrey Campus. She holds a Master's degree in Education with a specialization in Organizational Development from the Centro de Enseñanza Técnica y Superior (CETYS) University, Mexicali campus. She is a Chemical Environmental Engineer by profession, graduated from the Instituto Tecnológico de Mexicali. She has worked in the field of implementing international standards in both the private industry and the public sector, as well as implementing analytical techniques in potable and wastewater laboratories contributing to the livestock industry. She is a Federal Labor Inspector and a classroom teacher. Dedicated to teaching for 17 years, she has been at the Universidad Politécnica de Baja California in the Manufacturing Engineering area, with research contributions related to Sustainability, Environment, and Industrial Safety and Hygiene.

Fabian N. Murrieta-Rico received B.Eng. and M.Eng. degrees from Instituto Tecnológico de Mexicali (ITM) in 2004 and 2013 respectively. In 2017, he received his PhD in Materials Physics at Centro de Investigación Científica y Educación Superior de Ensenada (CICESE). He has worked as an automation engineer, systems designer, as a university professor, and as postdoctoral researcher at Facultad de Ingeniería, Arquitectura y Diseño from Universidad Autónoma de Baja California (UABC) and at the Centro de Nanociencias y Nanotecnología from Universidad Nacional Autónoma de México (CNyN-UNAM), currently he works as professor at the Universidad Politécnica de Baja California. His research has been published in different journals and presented at international conferences since 2009. He has served as reviewer for different journals, some of them include IEEE Transactions on Industrial Electronics, IEEE Transactions on Instrumentation, Measurement and Sensor Review. His research interests are focused on the field of time and frequency metrology, the design of wireless sensor networks, automated systems and highly sensitive chemical detectors.