Miguel Vieira obtained in 2017 his PhD in Leaders for Technical Industries (Engineering Design and Advanced Manufacturing focus area) by the Instituto Superior Técnico in partnership with the Massachusetts Institute of Technology under the MIT Portugal Program. Currently, he is an Assistant Professor at ISCTE - University Institute Lisbon, as a tenure-track lecturer and researcher in the fields of Operations and Supply Chains Management. His main topics of research expertise have been centered in the industrial management challenges of applied optimization methods and simulation models to solve supply chain, design, production planning and scheduling problems of complex manufacturing systems. In particular, the main research is focused at developing mathematical programming models, decomposition methods and non-exact approaches to provide optimal solutions to industrial cases, considering both deterministic and stochastic scenarios, with several first-author publications. Current research projects include the risk assessment of process design and planning, dynamic scheduling strategies for decisional tools in the context of Industry/Logistics 4.0 paradigm and methods for improving solutions of real-world industrial optimization problems. Particular relevance has been given to the efficient use of novel automation technologies in industrial and logistic processes, with the development of machine learning algorithms based in deep and reinforcement learning for novel interfaces for human-robot interaction/cooperation and its integration on the decision-support operations to increase flexibility and productivity as systems engineering approaches.