Eirinakis PavlosAssistant Professor


    Address: Bld of Industrial Management & Technology,
    107 Deligiorgi Str.,
    Piraeus, 185 34
    office 503, 5th floor
    Phone: +30 210 414-2390
    E-mail: pavlose(-at-)unipi(-dot-)gr
    Office Hours: By appointment


    10.2010: PhD in Operations Research, Department of Management Science & Technology, Athens University of Economics & Business
    06.2004: Master in Business Administration, Department of Business Administration & Department of Marketing & Communication, Athens University of Economics & Business
    06.2002: Bachelor in Informatics, Department of Informatics, Athens University of Economics & Business


    Pavlos Eirinakis is an Assistant Professor at the Department of Industrial Management and Technology, University of Piraeus. He graduated from the Department of Informatics in 2002 and received his MBA in 2004 from the Athens University of Economics and Business (AUEB). He fulfilled his PhD on structures, algorithms and applications of stable matching problems in 2010 in AUEB, Department of Management Science and Technology. He has worked as a Postdoctoral Research Fellow at the West Virginia University, where he examined issues related to computational logic, quantified linear systems and graph algorithms. He has also worked as a Senior Researcher at the AUEB applying analytical methods in Manufacturing and Logistics, as well as continuing his work on matching under preferences. Furthermore, he has worked as an R&D engineer in the maritime industry, designing and developing optimization systems. He has taught at an undergraduate and a postgraduate level at various Greek Universities. His research has been published in several international scientific journals (incl. Mathematics of Operations Research, Omega, Informs JOC, Journal of Manufacturing Systems, International Journal of Production Research, Algorithmica and others) and has been presented in various international scientific conferences. His research interests include the design and implementation of analytical methods in manufacturing and the maritime industry and their application through digital twins to support decisions.


    Modelling and optimization of industrial systems, application of analytical methods in manufacturing to identify/predict disruptions in production and to support decision to handle them, industrial digital twins, matching under preferences: theory and practice, graph algorithms, computational complexity and logic.

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