Professor Elena Papadopoulou is a faculty member at the Technical University of Crete within the School of Mineral Resources Engineering . Her research focuses on applied mathematics and computational science , addressing problems in groundwater dynamics, tumor modeling, and numerical methods for partial differential equations. Key Research Areas: Stochastic optimization for coastal aquifer management GPU-accelerated simulations for biomedical applications High-order numerical schemes for reaction-diffusion systems Unified transforms in multi-domain PDEs She has published extensively on saltwater intrusion modeling , brain tumor invasion , and parallel computing algorithms . Her work integrates mathematical modeling with environmental and medical challenges , emphasizing computational efficiency and environmental sustainability. Contact : epapadopoulou@tuc.gr
Dionysia Kolokotsa is a Professor in the Department of Environmental and Energy Management, Sustainable Development and Climate Change at the Technical University of Crete. She served as Dean of the CHEMIPER School from 2021 to 2024 and leads the Laboratory of Built Environment and Energy Management. Education: Ph.D. in Electronic & Computer Engineering (Technical University of Crete, 2001); MSc in Architecture Environmental Design (UCL, 1995); Postgraduate Certificate in Meteorology (National & Kapodistrian University of Athens, 1994); Degree in Physics (National & Kapodistrian University of Athens, 1991) Her research focuses on energy saving in buildings , indoor environment quality , and urban heat island mitigation . She has contributed to understanding thermal comfort in elderly populations , nature-based solutions for climate resilience , and smart grid integration . Notable awards include the Technical University of Crete Excellence Award (2021) and inclusion in the Stanford World's Top 2% Scientists (2020) . She serves as Editor-in-Chief of Solar Energy Advances and Advances in Building Energy Research , and is on the editorial boards of Energy and Buildings and Renewable Energy . Email: dkolokotsa@chenveng.tuc.gr, deniako@gmail.com Contact: Office K2.107, +30 28210 06104, +30 28210 37858 (FAX) Student reception hours: Daily 10:00-14:00
Giannakou Erasmia is an Assistant Professor at the Biomechanics Division within the Faculty of Physical Education and Sports Sciences at the Democritus University of Thrace . Her expertise lies in Biomechanics of health with a focus on Sports Training Theory & Application . Her research integrates biomechanical analysis, musculoskeletal modeling, and artificial intelligence applications in healthcare. Teaching responsibilities include academic supervision during office hours (Tue 15:00-18:00 & Wed 15:00-17:00). While formal education details are not provided, her work demonstrates advanced training in biomechanics and clinical movement analysis. Research interests span post-stroke gait mechanics , musculoskeletal modeling validation , AI-driven assessment tools , and athletic performance analysis . Her recent publications (2022-2025) emphasize machine learning applications in stroke rehabilitation, gait mechanics quantification, and biomarker development for neurological conditions. No awards or grants are explicitly listed. Her work frequently involves collaborations in stroke recovery mechanisms, wrestling biomechanics, and translational clinical research.
Alex Karagrigoriou is an Associate Professor of Statistics at the University of Piraeus, Department of Statistics and Insurance Science. He holds a BSc in Mathematics from the University of Patras, an MA and PhD in Mathematical Statistics from the University of Maryland, USA. His academic career includes roles at the University of Cyprus (1992–2014), the University of the Aegean (2014–2024), and adjunct positions at the Hellenic Open University (2014–present) and Mediterranean Institute of Management (1994–1998). Prior academic roles include work in the USA Department of Agriculture (1986–1992) and maritime sector experience (1980–1986). His research focuses on Applied Probability , Statistical Modeling , Reliability Theory , and Actuarial Mathematics . He has authored/co-authored over 100 journal articles, 10 edited volumes, and 40 conference proceedings, with notable contributions in divergence measures, semi-Markov processes, and risk modeling. His work has been cited over 1,400 times (h-index=17). Key achievements include supervising 3 postdocs, 6 PhDs, and 50 Master’s students, many of whom have received awards such as the Best Young Statistician Award (2007, 2018, 2021). His research trends emphasize stochastic modeling of complex systems, entropy-based inference, and interdependency patterns in econometric data. Labs/Teams: Active collaborator in interdisciplinary projects involving reliability engineering, biostatistics, and financial risk analysis. Serves as Co-Editor of Journal of Reliability and Statistical Studies and contributor to multiple international journals.
Livieris Ioannis is an Assistant Professor in the Department of Statistics and Insurance Science at the University of Piraeus. He holds academic positions including Adjunct Professorships at the University of the Peloponnese and Technological Educational Institute of Western Greece. His research focuses on optimization methods for neural networks, machine learning, ensemble techniques, and their applications in healthcare, finance, education, and environmental science. Education: Ph.D. in Mathematics (2012), University of Patras M.Sc. in Computational Mathematics & Informatics in Education (2008), University of Patras B.Sc. in Mathematics (2006), University of Patras Research Interests: Dr. Livieris specializes in developing optimization algorithms for neural networks, semi-supervised learning, and ensemble methods. His work emphasizes practical applications such as time series forecasting (financial, environmental), medical image analysis (cancer detection, X-ray classification), and educational data mining (student performance prediction). He also explores explainable AI frameworks to enhance transparency in deep learning models. Key Contributions: He has contributed to over 50 peer-reviewed articles, including work on weight-constrained neural networks, gradient-based optimization, and CNN-LSTM models for cryptocurrency forecasting. His research has been recognized with inclusion in Stanford’s top 2% scientists (2020–2023) and a best paper award at HERCMA ’09. Awards & Roles: Associate Editor, Evolving Systems (Springer) Reviewer for 50+ journals including Neurocomputing and IEEE Transactions on Neural Networks Grants & Projects: Principal investigator in EU-funded projects like NEUROCLIMA (climate resilience via AI), ORBIS (democratic participation via AI), and PVAdapt (sustainable energy systems). He also leads initiatives in explainable AI for medical imaging and causal effect estimation in social science. Labs & Teams: Active in interdisciplinary teams at the University of Piraeus, focusing on AI-driven solutions in education, healthcare, and environmental monitoring. Collaborates with institutions like the IEEE and the Hellenic Association of ICT in Education.
Olympia PANAGOULI is an Assistant Professor in the Department of Civil Engineering at the University of Thessaly. She holds a Diploma in Civil Engineering from the National Technical University of Athens (1988) and a Doctoral Thesis from Aristotle University of Thessaloniki (1992), focusing on fractal geometry in structural analysis. Her academic roles include teaching Structural Analysis III, Elastoplastic Analysis, and Finite Elements at the University of Thessaly since 2007. She has extensive experience in structural analysis projects (1992-2007) and has been a lecturer in structural engineering at both Architectural and Civil Engineering departments of the University of Thessaly from 1999 to 2007. Professional Address: Dept. of Civil Engineering, University of Thessaly, Pedion Areos, 38334 Volos, Greece Phone: +302421074146 Email: olpanag@uth.gr Her research interests focus on applying fractal geometry to civil and structural engineering problems, including numerical methods, fractal interfaces, contact mechanics, and material behavior. She has actively participated in national and international research programs since 1989, addressing topics like nonsmooth mechanics, composite materials, and fractal data compression. Panagouli has also contributed to international conferences on computational mechanics, contact mechanics, and structural analysis since the early 1990s. Her computing expertise includes programming languages like FORTRAN and C, and operating systems such as UNIX and Windows. She has reviewed journals like Computers and Structures and Engineering Structures . Panagouli’s work emphasizes the intersection of fractal theory with civil engineering applications, addressing complex structural problems through innovative numerical techniques.
Professor Ilias Maglogiannis is a leading academic in Computational Biomedicine at the University of Piraeus , directing its Computational Biomedicine Laboratory. He holds a PhD from the National Technical University of Athens and has held faculty positions at the University of the Aegean and University of Thessaly before joining the University of Piraeus in 2013. He has served as Dean and Department Chair, leading large-scale EU projects like AI4WORK and MELIORA . His research focuses on AI in Healthcare , including medical imaging, wearable devices, and telemedicine systems. He has published over 400 papers (h-index 46), three books, and serves on editorial boards of journals like IEEE JBHI and Personal and Ubiquitous Computing . Key Awards: Fellow of EAMBES, Senior IEEE Member Leadership: IFIP WG12.5 President (AI Applications) Current Projects: MedSecurance (IoMT security), E-Prevention (mental health monitoring) His teaching includes courses on Pattern Recognition , Telemedicine , and Digital Image Processing . He actively promotes AI ethics and human-centric digital twin technologies in healthcare and education sectors.
Ioannis Vogiatzis is a Professor and Chair of the Department of Computer Engineering at the University of West Attica . He serves as Director of the Computer and Embedded Systems, Internet of Things, and Optimization (CESIO) Laboratory. Education: B.A. in Computer Science (1990) MSc in Electronic Automation (1994) Ph.D. in Computer Science (1998) Research interests focus on dependability and security of digital systems , reconfigurable computing , and accelerator design for artificial intelligence. He also explores machine learning and AI algorithms , blockchain systems , Internet of Things (IoT) , and unmanned aerial vehicles (UAVs) . Grants & Projects: He has participated in multiple projects funded by the European Union and the Greek government. Labs & Teams: He leads the CESIO Laboratory, specializing in computer engineering, embedded systems, IoT, optimization, and AI-driven security solutions.
Ioannis Papamichael is a Professor at the School of Production Engineering and Management of the Technical University of Crete. His expertise lies in Mathematical Programming and Algorithms , focusing on Nonlinear Programming, Absolute Optimization, and Optimal Control of Highway Networks. He is affiliated with the Decision Science Laboratory . Education: PhD in Process Systems Engineering, Imperial College London (2002) MSc in Process Systems Engineering, Imperial College London (1999) Diploma in Chemical Engineering, National Technical University of Athens (NTUA, 1998) Research Interests: His work addresses advanced optimization methodologies, with particular attention to real-world applications in transportation systems and decision science. He explores theoretical frameworks for nonlinear systems and their practical implementation in highway control mechanisms. Affiliations & Activities: Collaborates through the Decision Science Laboratory, contributing to interdisciplinary research. Office hours are arranged upon request (Office D5.102, contact via pem_info@tuc.gr ).
George P. Kafentzis is a Lecturer in the Computer Science Department at the University of Crete, where he teaches Physics for Engineers (CS-112), Digital Signal Processing (CS-370), and Signals and Systems (CS-215). He is a core member of the Speech Signal Processing Lab within the Multimedia Informatics Labs, focusing on advanced signal processing methodologies. His educational background includes a Ph.D. in Signal Processing and Telecommunications from MATISSE Doctoral School (University of Rennes 1) and a Ph.D. in Computer Science and Engineering from the University of Crete (2014), a Master of Science in Computer Science (2010), and a Bachelor's degree in Computer Science (2008), all from the University of Crete. Research interests span speech, audio, and biosignal processing with emphasis on sinusoidal modeling, emotion recognition from speech, deep learning applications, pathological speech analysis, and music signal processing. His work bridges theoretical signal processing with clinical and engineering applications, particularly in non-invasive vocal fold pathology detection through glottal analysis. Recent publications demonstrate a strategic pivot toward cough sound analysis for respiratory diagnostics using AI, while maintaining core expertise in adaptive sinusoidal models for speech transformations. Publication trends reveal an evolution from fundamental speech modeling (2010-2016) toward applied health informatics (2021-present), with increasing focus on real-world diagnostic systems leveraging cough acoustics. Over 50% of recent work integrates deep learning with traditional signal processing for medical applications, particularly in low-resource settings. Graduate student Scholarship - Institute of Computer Science, FO.R.T.H. (2008-2010) Undergraduate Scholarship - Institute of Computer Science, FO.R.T.H. (2007-2008) As an active industry collaborator, Kafentzis has served as Signal Processing Engineer at Hyfe AI (2022-2025) and contractor for VoiceSignals and Toshiba Research Europe. His teaching portfolio includes a widely adopted textbook Continuous and Discrete Time Signal Processing (2019), which integrates MATLAB implementations with theoretical foundations. Current research leverages his signal processing expertise in cough monitoring systems validated through multicenter clinical trials. He leads projects in the Speech Signal Processing Lab including Novel Deep Learning Architectures for Automatic Speech Recognition and Speech Emotion Recognition and Visualization Techniques, with recent work extending to Greek-language pathological speech analysis and respiratory health monitoring systems.
Dr. Panagiotis Repoussis serves as Associate Professor of Operations Research and Supply Chain Management at the Department of Marketing and Communication within the School of Business at Athens University of Economics and Business (AUEB). Previously, he held positions as Assistant Professor at Stevens Institute of Technology and visiting Lecturer at the University of Piraeus and Bayes School of Business at City University of London. His academic foundation includes a Diploma in Chemical Engineering from the National Technical University of Athens (2002), followed by graduate studies at Imperial College London and AUEB where he completed his doctoral dissertation in November 2008. His educational trajectory reflects a strategic shift from chemical engineering to operations research specialization. Dr. Repoussis specializes in Operations Research with concentrated expertise in Supply Chain Management , Vehicle Routing and Scheduling , and Production Systems Optimization . His research integrates mathematical modeling with computational intelligence to solve complex combinatorial optimization problems across logistics networks, manufacturing operations, and transportation systems. Key methodological contributions include advanced algorithms for dynamic scheduling under uncertainty and real-time decision support frameworks. Analysis of his 15 most recent publications (2019-2025) reveals a strong research trajectory toward Industry 4.0 applications, with increasing focus on IoT/AGV integration in manufacturing, disruption-resilient logistics, and robust optimization under stochastic conditions. Vehicle routing problems remain his dominant research theme, now extended to cross-docking operations, profit-oriented routing, and humanitarian logistics contexts. As principal investigator, Dr. Repoussis has secured research funding from NSF, EU programs, non-profit organizations, and private sector partners across Europe and North America. His academic service includes editorial board membership for Transportation Research Part E and Advances in Operations Research, leadership roles in the Hellenic Operational Research Society and Production and Operations Management Society, and organization of major conferences including Odysseus and MathSports. His professional activities demonstrate deep engagement with both theoretical advancements and practical implementations, particularly through development of decision support systems for waste management, healthcare logistics, and energy-aware production scheduling. Current initiatives emphasize the convergence of prescriptive analytics with emerging digital technologies in operational planning contexts.
Panagiotis Papastamoulis serves as Assistant Professor at the Department of Statistics within the School of Information Sciences and Technology at Athens University of Economics and Business (AUEB). He joined AUEB in April 2020 after working as an Adjunct Lecturer from 2018-2019 and completing extensive postdoctoral research at prestigious institutions including the University of Manchester (2012-2018) and INRA in France (2011-2012). His educational background includes a BSc in Mathematics from the University of Patras (2003), an MSc in Applied Statistics (2006), and a PhD in Statistics (2010) from the University of Piraeus. His doctoral thesis addressed the label switching problem in Bayesian analysis of mixtures of distributions under the supervision of Professor G. Iliopoulos. Dr. Papastamoulis's research program centers on Bayesian and computational statistics, with particular expertise in finite mixture models, model-based clustering, and bioinformatics applications. His methodological contributions span theoretical developments in label switching solutions, reversible jump MCMC algorithms, and practical implementations for RNA-seq data analysis. His work demonstrates a consistent trajectory from foundational statistical theory to real-world biological applications. Analysis of his publication record reveals a strong focus on developing statistical methodology for complex data structures, with significant contributions to mixture modeling, Bayesian factor analysis, and bioinformatics. His most recent work (2023-2025) extends into cure rate modeling, directional data analysis, and multinomial mixture models for spatial data, showing continued innovation while maintaining connections to his core research themes. As an educator, he teaches undergraduate courses including Linear Models and Bayesian Inference Methods, and graduate courses such as Statistical Genetics-Bioinformatics and High Dimensional Statistics. He has also developed multiple open-source R packages that have become standard tools in the statistical community, including label.switching, BayesBinMix, and fabMix, which address fundamental challenges in mixture model analysis. Dr. Papastamoulis actively contributes to the academic community through organizing research seminars at AUEB and participating in conference committees, including the 22nd European Young Statisticians Meeting in 2021. His research integrates theoretical statistical development with practical computational implementations, creating tools that advance both methodology and application in multiple scientific domains.
Panos Louridas is a Professor at the Department of Management Science and Technology, Athens University of Economics and Business. His work spans software engineering, algorithms, security, and systems implementation, with global impact through publications and the Zeus e-voting system. He is affiliated with leading academic societies including ACM, IEEE, Usenix, and AAAS. Education : Graduate of the Department of Informatics, University of Athens; MSc by Research and PhD from the University of Manchester. His research focuses on practical algorithm applications, secure systems design, and big data implementations. He actively develops software, notably the Zeus e-voting system used internationally. With over 1,600 citations, his work bridges theoretical and applied computer science. Scientific Awards and Memberships : Member of the Association for Computing Machinery (ACM) Institute of Electrical and Electronics Engineers (IEEE) Usenix American Association for the Advancement of Science (AAAS) Louridas has authored the textbook Real World Algorithms (MIT Press) and is working on Algorithms (The MIT Press Essential Knowledge Series) . His contributions to academia and technology are complemented by his role in designing real-world systems.
Vasileios Megalooikonomou serves as a Professor at the Department of Computer Engineering and Informatics within the School of Engineering at the University of Patras. He directs the Multidimensional Data Analysis and Knowledge Management Laboratory and maintains active teaching responsibilities across undergraduate and postgraduate programs. His research spans several interconnected domains in computer science and information systems. Dr. Megalooikonomou's work focuses on foundational database technologies while extending into advanced applications through Intelligent Information Systems and Data Mining . His expertise encompasses both theoretical frameworks and practical implementations in Pattern Recognition and Data Compression , with specialized applications in Biomedical Informatics and Multimedia systems. This multidisciplinary approach bridges traditional database theory with contemporary computational challenges. Within the University of Patras infrastructure, he leads the Multidimensional Data Analysis and Knowledge Management Laboratory , which serves as the operational hub for his research activities. His teaching portfolio includes core database courses (Databases I, Databases II, Database Laboratory), advanced algorithmic instruction (Data Mining and Learning Algorithms), and specialized postgraduate topics focusing on Spatial and Temporal Databases and Knowledge Mining. Office hours are maintained on Monday 11:00-13:00 and Wednesday 13:00-14:00 for student consultation.
Evi Papaioannou is an Assistant Professor at the Department of Computer Engineering and Informatics , University of Patras. Her research focuses on foundational and applied aspects of algorithms, computational complexity, and distributed systems, with interdisciplinary applications in education and the humanities. Researcher at the Computer Technology Institute & Press (CTI "Diophantus") Teaches courses like Theory of Computation , Parallel Algorithms , and Computational Complexity Research Interests span algorithmic design, wireless networks, game theory, and pedagogical approaches to computational thinking. She also integrates theoretical computer science into educational technology and humanities. Her affiliations include the Division of Applications and Foundations of Computer Science , which oversees research in fundamental principles and emerging areas like high-performance computing, artificial intelligence, and multimedia networks. She contributes to laboratories in combinatorial algorithms, distributed systems, and machine learning.
