Dr. Ioannis Markoulidakis
Dr
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Academic Career Length
7Years (2020-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Journal Article
Ioannis MarkoulidakisIRIoannis Rallis
Ioannis RallisIGIoannis Georgoulas
Ioannis GeorgoulasGKGeorge Kopsiaftis
George KopsiaftisNDNikolaos Doulamis
Nikolaos DoulamisNDNikolaos Doulamis
Nikolaos DoulamisThe current paper presents a novel method for reducing a multiclass confusion matrix into a version enabling the exploitation of the relevant performance metrics and methods such as the receiver operating characteristic and area under the curve for the assessment of different classification algorithms. The reduction method is based on class grouping and leads to a special type of matrix called the reduced confusion matrix. The developed method is then exploited for the assessment of state of the art machine learning algorithms applied on the net promoter score classification problem in the field of customer experience analytics indicating the value of the proposed method in real world classification problems.
Journal Article
Ioannis MarkoulidakisGMGeorgios Ioannis Markoulidakis
Georgios Ioannis MarkoulidakisThe paper addresses the issue of classification machine learning algorithm performance based on a novel probabilistic confusion matrix concept. The paper develops a theoretical framework which associates the proposed confusion matrix and the resulting performance metrics with the regular confusion matrix. The theoretical results are verified based on a wide variety of real-world classification problems and state-of-the-art machine learning algorithms. Based on the properties of the probabilistic confusion matrix, the paper then highlights the benefits of using the proposed concept both during the training phase and the application phase of a classification machine learning algorithm.
Journal Article
Ioannis MarkoulidakisIRIoannis Rallis
Ioannis RallisIGIoannis Georgoulas
Ioannis GeorgoulasGKGeorge Kopsiaftis
George KopsiaftisNDNikolaos Doulamis
Nikolaos Doulamis
Anastasios DoulamisCustomer Experience (CX) is monitored through market research surveys, based on metrics like the Net Promoter Score (NPS) and the customer satisfaction for certain experience attributes (e.g., call center, website, billing, service quality, tariff plan). The objective of companies is to maximize NPS through the improvement of the most important CX attributes. However, statistical analysis suggests that there is a lack of clear and accurate association between NPS and the CX attributes’ scores. In this paper, we address the aforementioned deficiency using a novel classification approach, which was developed based on logistic regression and tested with several state-of-the-art machine learning (ML) algorithms. The proposed method was applied on an extended data set from the telecommunication sector and the results were quite promising, showing a significant improvement in most statistical metrics.
26 June 2024
Conference Paper
GKGeorge Kopsiaftis
George KopsiaftisIKIason Katsamenis
Iason KatsamenisIRIoannis Rallis
Ioannis RallisNBNikolaos Bakalos
Nikolaos BakalosCZCharalampos Zafeiropoulos
Charalampos ZafeiropoulosSCStephanos Camarinopoulos
Stephanos Camarinopoulos +11
In recent years, there has been a notable rise in the adoption of Unmanned Aerial Vehicles (UAVs) for infrastructure inspection. This study focuses on presenting IKAROS, an integrated system that harnesses the combined capabilities of multiple UAVs and deep learning (DL) tools to improve the efficiency of road transport network inspections, facilitate the detection of road defects, and manage traffic emergencies. Specifically, we introduce the IKAROS system, outlining its key components and functionalities, with a particular emphasis on the applied technologies and the interconnections of its various systems. In addition, we provide an overview of the pilot site and address the challenges associated with real-world implementation.
About Me
Dr Yannis Markoulidakis, received his Dipl.-Ing. & PhD degrees in Electrical Engineering from the National Technical University of Athens, Greece in 1990 and 1994 respectively. During 1990-1998 he worked as a senior research engineer in NTUA (Telecommunications Laboratory) and on 1998 he joined Vodafone Greece. In the period 2000-2009 he has been Head of Technology Strategic Planning-R&D Department and member of Vodafone Group R&D Management Team. In 2009-2016 he held various managerial positions including Commercial Strategy Senior Manager, Products & Services Senior Manager and Customer Experience Leadership Senior Manager. Since 2016 Dr Markoulidakis is collaborating with innovative SMEs for the commercialization of innovative ideas. Dr Markoulidakis has a broad experience both in R&D projects in the areas of telecommunications, Information Technology, product development (agile, scrum methodologies), commercial strategy and customer experience. He has >75 publications in scientific journals and conferences, invited presentations to conferences and filed 7 patents. Moreover, Dr Markoulidakis has been acting as a reviewer for scientific journals and numerous of EU framework programs.