Antonio Padovano received his Master Degree in Management Engineering Summa cum Laude and Ph.D. in Industrial Systems Engineering at the University of Calabria (Italy) where he is currently Post-Doc and Teaching Assistant. During his PhD, he carried out research activities as Pre-Doctoral Research Fellow at the Beth Israel Deaconess Medical Center, teaching hospital of the Harvard Medical School and at the Massachusetts Institute of Technology’s Zaragoza Logistics Center. He also actively cooperates (or cooperated) with several research institutions, organizations and companies worldwide, including NASA KSC, NATO STO CMRE, Rutgers University. He is also a Guest Editor of different international journals’ special issues in the field of Applied Mathematics, Modeling & Simulation and Computer Science and a member of the Editorial Board of the International Journal of Simulation and Process Modeling and International Journal of Oil, Gas and Coal Technology. He participated in several conferences as a speaker, authored and peer-reviewed articles for conferences and journals. He is Program Chair of the International Conference on Industry 4.0 and Smart Manufacturing (ISM) and member of the IPC and Organizational Committee of the I3M Multiconference.

Antonio’s research interests are mainly devoted to the design, analysis, and optimization of industrial and logistic systems, with specific reference to:

i. the design and development of Industry 4.0 solutions for intelligent management and performance optimization of Smart Factories and logistics systems;
ii. interoperable simulation- & AI-based systems based on mixed reality technologies for supporting decision making as well as for enhancing education & training in Industry, Logistics, Healthcare, and Defense, with a focus on Disaster management;
iii. analysis and modeling human performance, reliability and unpredictability in industrial processes based on cognitive, psychological and health predictors, by leveraging on different modeling paradigms (e.g. knowledge-based systems, agent-based simulation, fuzzy logic, neural networks.