Computational and Deep Learning Models for Advanced Behavioral Analysis

The use of cutting-edge artificial intelligence (AI) techniques to understand, predict, and interpret complex human behaviors is essential in deep learning models. By leveraging deep learning architectures and computational modeling, researchers and practitioners can uncover patterns in diverse datasets from consumer behavior to cognitive and emotional responses. These intelligent systems enable more accurate behavioral insights, supporting applications in psychology, healthcare, marketing, security, and human-computer interaction. Through the fusion of computational power and behavioral science, they are revolutionizing the way we analyze and respond to human behavior in an increasingly data-driven world. Computational and Deep Learning Models for Advanced Behavioral Analysis explores the integration of computing models and deep learning techniques in the analysis of behavioral data. It highlights recent advances in interpretable AI, reinforcement learning, sequential modeling, and simulation techniques tailored for behavioral contexts. Covering topics such as deep learning models, behavioral analysis, and computational intelligence, this book is an excellent resource for researchers, practitioners, and graduate students.

Dr. Ali Turab (IEEE Member) is an Associate Professor at the School of Software, Northwestern Polytechnical University (NPU), China. He holds a Ph.D. in Applied Mathematics from Thammasat University, Thailand, where he also completed postdoctoral research focused on nonlinear modeling and dynamical systems. He has previously served as a Research Associate at the Centre of Excellence for Artificial Intelligence & Data Science at Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), Malaysia. His research interests lie at the intersection of mathematical modeling, artificial intelligence, and behavioral sciences, with a particular emphasis on the computational modeling of natural phenomena and cognitive behavior. He integrates game theory, decision-making analysis, probabilistic machine learning models, and cognitive neurodynamics to study adaptive and goal-directed behavior in animals and intelligent systems. His recent work explores hybrid neural-stochastic models and reinforcement learning methods to analyze behavioral dynamics and decision-making under uncertainty. Dr. Turab is actively involved in interdisciplinary research and academic mentorship, contributing to high-impact publications and collaborative projects across applied mathematics, AI, and behavioral prediction.

Josué Antonio Nescolarde Selva , professor at the Department of Applied Mathematics at the University of Alicante, is the author of more than 100 scientific publications (most of them JCR indexed in the Science Citation Index). He has directed a total of 5 doctoral theses (1 with International Mention, 2 as the only supervisor, one of them Extraordinary Doctorate Award). In 2017, he received recognition as a researcher in his field from the University of Alicante, with the highest number of scientific publications indexed in the Web of Science in 2015. His lines of research are developed, mostly, in the fields of Biomathematics, Cybernetics, Data Science and Philosophy of Science, collaborating in a large part of his publications on a stable basis with members of his research group, as well as with researchers from various institutions from different parts of the world among which we find: Dublin City University, Ireland; Northeast Normal University, China; University of Georgia, USA. Among other examples of leadership, he has also been appointed as Guest Editor-in-Chief to several special issues in various JCR journals, including Kybernetes, Cybernetics, and Systems and Foundations of Science; as well as being appointed to several editorial teams, including the JCR journals: International Journal of General Systems and Applied Artificial Intelligence. He has participated in a total of 7 research projects in competitive calls, 4 of them corresponding to the National Plan. He has been involved in 6 contracts with companies and 2 projects (1 national and 1 regional) in the field of knowledge transfer, dissemination, and exchange. He has carried out a total of 5 postdoctoral research stays at universities that occupy leading positions at an international level in the most recognized rankings: Northeast Normal University, Changchun, China, and Northwestern Polytechnical University, Xian, China. At the teaching level, he has given more than 5000 official teaching hours at the different levels of education, teaching Mathematics at all possible levels: from the previous programs of bachelor’s degree plans, technical engineering, and higher engineering to the new bachelor's and master's degrees. He has participated in numerous teaching innovation projects. In all the teaching evaluations carried out, before and after the DOCENTIA program, the results have been very favorable. In the academic years 2012/2013 and 2013/2014, he was selected as the most valued professor at his center by the students of all the degrees in which he teaches. From the 2012/2013 academic year to the 2020/2021 academic year, he led the Tutorial Action Program (PAT) at the Polytechnic School. Since 2013, and on an ongoing basis, he has held various individual university management positions, all of them at the School level, developing his activity in various areas such as postgraduate studies, working on the coordination of the master's degrees that are taught as well as in the launching of new degrees; in the area of communication, in the organization of different activities with the aim of giving greater visibility to the School as well as in relations with the students of the center and the management team of the School. His leadership in this area is supported by his experience as Deputy Director of the School from 2017 to the present.