Dr. Luis Gustavo Nardin is an associate professor in the Department of Computer Science and Intelligent Systems at IMT Mines Saint-Étienne (MSE) and a member of the Laboratory of Informatics, Modelling and Optimization of the Systems (LIMOS UMR 6158). He holds a M.Sc. (2009) and Ph.D. (2015) degrees in Electrical Engineering with specialization in Artificial Intelligence from the University of São Paulo, Brazil. He teaches multi-agent system (MAS), software engineering, and cloud computing courses to the undergraduate students and the Cyber-Physical and Social Systems (CPS2) master students at MSE.
His main research interests are models, tools, and methodologies for the regulation of MAS. He also conducts research on agent-based simulation focused on understanding the impacts of social and human behaviors and institutional policies on the emergent properties of complex adaptive systems. Dr. Nardin has previously held faculty positions in the School of Computing at the National College of Ireland and the Brandenburg University of Technology in Cottbus, Germany, after spending some time in a Postdoctoral Fellowship position at the Center for Modeling Complex Interactions at the University of Idaho, USA. Dr. Nardin is the coordinator of the international project ANR-FAPESP Normative Artificial Intelligence for Regulating Manufacturing (NAIMAN) in collaboration with the University of São Paulo, developing normative models and mechanisms for regulating the manufacturing industry. He also leads the organization of the Summer School on AI Technologies for Trust, Interoperability, Autonomy and Resilience in Industry 4.0 (AI4Industry) in collaboration with a broad range of academic institutions and industrial partners.
He participates in the ANR-SNF HyperAgents project in developing regulation ontologies and mechanisms for supporting the deployment of world-wide hybrid communities of people and artificial agents on the Web, and in the ANR ACCELER-AI project at developing models and mechanisms for the multi-faceted bounding of the learning of ethical behavior.