Georgios Bardis is a permanent Assistant Professor at the Department of Informatics and Computer Engineering , School of Engineering , University of West Attica . He holds a PhD in Informatics from University of Limoges (2006), an MSc in Software Systems from University of California, Santa Barbara (1994), and a Diploma in Computer Engineering & Informatics from University of Patras (1992). His career spans multiple academic roles, including Lecturer at University of West Attica (2018-2021) and Professor of Applications at TEI of Athens (2010-2018). Research Interests : Focus on Intelligent Computer Graphics , Declarative Modeling , and Multicriteria Decision Analysis . His work integrates AI into 3D scene synthesis, urban planning, and semantic decision systems. Awards : Master Microsoft Office Specialist (MOS), 2003 NAT Scholarships for Academic Excellence (1989-1992) 1984 Monetary Prize from Hellenic Mathematical Society Leadership : Member of AKIIS Research Lab (University of West Attica), Editorial Board of International Journal of Systems Biology and Biomedical Technologies , and Reviewer for International Journal of Digital Earth . Publications : 5 peer-reviewed journals, 2 books, 8 book chapters, and 22 conference papers. Key areas include WebGL avatars, urban data analysis, and 3D modeling with AI.
Dr. Sotirios Koukoulas is an Associate Professor at the Department of Spatial Planning, Urban Planning and Regional Development at the University of Thessaly since 2023. His academic career spans over 20 years, including roles as Lecturer (2002–2023) and Postdoctoral Researcher (2001–2002) at the University of the Aegean. He holds a PhD in Remote Sensing and GIS from King’s College London, an MSc in Statistics from the University of Lancaster, and a Bachelor’s in Environmental Science from the University of the Aegean. Research Interests: Remote Sensing and GIS applications for land use/cover change Coastal erosion modeling and climate change impacts Urban growth analysis and sprawl monitoring Environmental degradation and desertification mapping Spatial metrics in ecological and urban planning Key Academic Contributions: Pioneered GIS models for landfill site selection and coastal resilience Developed integrated coastal simulation tools (SCAPEGIS) Created statistical frameworks for extremal dependence in coastal systems Advanced land cover classification using machine learning (Random Forests) Contributed to EU climate cost assessment projects (ClimateCost, CIRCE) Scientific Recognition: Recipient of Marie Curie Outgoing International Fellowship Member of editorial boards for PLOS One and Remote Sensing journals Active in international conference scientific committees (EARSeL, IGARSS) Collaborated with institutions in the UK, Ireland, Germany, and China Teaching and Leadership: Lectures on Remote Sensing, Statistics, and Land Cover Mapping Coordinator of university research grants and EU-funded projects Advisor for graduate students in environmental and urban studies
Prof. Vana Kalogeraki is a Faculty Member at the Department of Informatics , Athens University of Economics and Business (AUEB) , and serves as the Dean of the School of Information Sciences and Technology and Director of the Computer Systems and Communications Laboratory . She has held academic positions at the University of California, Riverside and was a Research Scientist at Hewlett-Packard Labs . PhD: University of California, Santa Barbara M.S. & B.S.: University of Crete, Greece Her research focuses on Distributed and Real-Time Systems , Big Data Systems , Cloud Computing , Human-Centered Systems , and Crowdsourcing . She has published over 200 papers at top journals (IEEE TPDS, ACM TOS, etc.) and conferences (RTSS, DSN, ICDCS, VLDB, MDM), including co-authoring the OMG CORBA Dynamic Scheduling Standard . Her 2023-2025 publications address AI pipelines in serverless environments, edge computing for trauma detection via eye-tracking, and fairness in resource scheduling. She has received prestigious awards including an ERC Starting Grant , Best Paper Awards (DEBS 2017, IPDPS 2009), a Best Poster Award (EuroSys 2024), and multiple UC Research Awards . Her research is funded by the European Union (ARISTEIA, THALIS), NSF, and industry partners like SUN and Nokia. Advising Legacy : Supervised 10 PhD graduates (now at Google, Amazon, IBM, Apple) and over 60 MS/PhD committees Labs & Teams : Leads the Computer Systems and Communications Laboratory at AUEB, focusing on mobile human-centered systems and urban data analytics
Georgios Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He holds a PhD from the National Technical University of Athens and has been a faculty member at the University of Ioannina since 2002, progressing from Lecturer to Associate Professor in 2018. He has also served as temporary teaching staff at the University of Patras, University of Crete, and University of Ioannina in the late 1990s and early 2000s. Education: B.Sc. in Computer Engineering (Diploma), National Technical University of Athens (NTUA), 1987–1992 MSc in Advanced Methods in Computer Science (Distributed and Parallel Systems), Queen Mary, University of London, 1992–1993 PhD in Computer Engineering, NTUA, School of Electrical and Computer Engineering, 1993–1997 His research interests lie at the intersection of Biomedical Engineering and Computing Systems , with a strong emphasis on Biomedical Signal Processing , Entropy Analysis , and Machine Learning . He has pioneered work in Bubble Entropy —a parameter-free entropy measure—and developed fast algorithms for entropy computation. His work also extends to compiler design and parallel computing, particularly in the automatic parallelization of recursive functions and loops. The trends in his recent publications reflect a dual focus: (1) biomedical applications involving entropy, heart rate analysis, and disease diagnosis using machine learning (especially Random Forests and SVMs), and (2) high-performance computing, including parallelization techniques and compiler optimizations for multi-core and SVP architectures. His research is highly interdisciplinary, combining signal processing, algorithm design, and clinical applications. Scientific Leadership and Recognition: Guest Editor, Special Issue on “Entropy in Biomedical Engineering”, Entropy (MDPI) Member of the IPAN Laboratory, University of Ioannina Active contributor to IEEE, Elsevier, and MDPI journals He has supervised several graduate students and is involved in funded research projects such as Palimpsest and Homore , focusing on smart systems for cultural interaction and elderly monitoring. His advising contributions are evident in co-authored papers with students like Evanthia Tripoliti and Aristeidis Mastoras. He teaches both undergraduate and postgraduate courses, including Compilers I/II and Biomedical Data Analysis . Laboratories and Teams: He is a member of the IPAN lab at the University of Ioannina, which supports interdisciplinary research in informatics and biomedical applications. His collaborative network includes researchers from Greece and abroad, particularly in the fields of biomedical signal analysis and entropy-based methods.
Georgios Petropoulos is an Assistant Professor of Geoinformatics at the Department of Geography, Harokopio University of Athens, Greece, where he has been teaching since 2020. His expertise spans Earth Observation technology, Geographic Information Systems, and remote sensing applications for environmental monitoring and geohazard assessment. He has previously held academic positions at Aberystwyth University in the UK and has been involved in numerous research projects related to land surface process modeling and remote sensing. His educational background includes: PhD in Earth Observation Modelling from King's College London, University of London (2008) MSc in Remote Sensing from the intercollegiate program between University College London, King's College London, and Imperial College (2002) BSc in Natural Resources Development & Agricultural Engineering from the Agricultural University of Athens (1999) Dr. Petropoulos specializes in the application of Earth Observation technology for understanding land surface interactions and feedback processes. His research focuses on utilizing remote sensing synergistically with land surface process models to derive key state variables of the Earth's energy balance and water budget. He has extensive experience in using advanced remote sensing technology for land use/cover mapping, vegetation properties retrieval, and geohazard assessment including floods, wildfires, and frost events. His work also involves developing open-source software tools for Earth Observation and implementing comprehensive benchmarking approaches for remote sensing algorithms. Dr. Petropoulos has received numerous prestigious awards and fellowships throughout his career, including: Marie Curie Individual Fellowship (2017) Senior Fellow of the UK Higher Education Academy (2015) Marie Curie Reintegration Grant (2013) European Space Agency fellowship (2010) Excellent Associate Editor Award for journal Environmental Modelling & Software (2021) Best conference poster award at the Asian Conference on Remote Sensing (2018) As an educator, Dr. Petropoulos has taught undergraduate and postgraduate courses in cartography, geoinformatics, remote sensing, and GIS at multiple institutions including Harokopio University, Aberystwyth University, and the Agricultural University of Athens. He has secured competitive research funding from various sources including the European Commission, ESA, and national research councils. His editorial work includes serving as an editor for Elsevier's Book series in "Earth Observation" and as an editorial board member for several international journals. Dr. Petropoulos is actively involved in international research collaborations and has contributed to numerous scientific committees and working groups related to Earth Observation standards and validation approaches. His current research continues to advance methodologies for soil moisture retrieval, land surface temperature estimation, and environmental monitoring using multi-sensor remote sensing approaches.
Ioannis Vlahavas is a Professor in the School of Informatics at Aristotle University of Thessaloniki since 2003, where he directs the Intelligent Systems Lab. He has held significant leadership roles including Chair of the School of Informatics (2003-2005, 2013-2017) and Dean of the School of Science and Technology at the International Hellenic University (2007-2016). His career spans over three decades with continuous contributions to artificial intelligence research and education. Education: Ph.D. in Computer Science, Aristotle University of Thessaloniki (1988) B.Sc. in Physics, Aristotle University of Thessaloniki (1982) Professor Vlahavas's research focuses on foundational AI areas including Logic Programming, Knowledge Representation and Reasoning, Automated Planning, and Machine Learning. His work bridges theoretical frameworks with practical applications in autonomous systems, healthcare diagnostics, and financial modeling. He has pioneered methodologies in reinforcement learning and multi-agent systems, with particular emphasis on personality emulation in gamified environments and transformer-based architectures for complex real-world problems. His recent publications reveal a strong trajectory toward deep reinforcement learning, transformer optimization, and low-resource language processing. Key application domains include autonomous driving (5 of 15 recent papers), biomedical text mining (particularly drug-drug interaction extraction), and personality modeling in gaming environments. There is notable cross-pollination between finance (portfolio theory applications, cryptocurrency trading) and AI methodology development. Scientific Awards: EurAI Fellow (2017) Professor Vlahavas has mentored numerous graduate students through PhD candidate programs and research projects. His leadership extends to organizing major international conferences including the 24th IEEE International Conference on Tools with AI (2012) and the 9th Hellenic Conference on Artificial Intelligence (2016). He serves on editorial boards and has guest-edited special journal issues on AI applications. He directs the Intelligent Systems Lab at Aristotle University, which operates as a multidisciplinary research hub focusing on machine learning, natural language processing, and intelligent system applications across healthcare, transportation, and finance sectors. The lab maintains strong industry connections including RealMINT, the university spin-off where he serves as CEO.
Panagiotis Kasnesis is a Senior Research Fellow at the Department of Electrical & Electronics Engineering, University of West Attica. He holds a Ph.D. in Computer Science from NTUA, alongside degrees in Chemical Engineering and Techno-Economic Systems. His research focuses on machine/deep learning, Semantic Web technologies, multiagent systems, and IoT, with over 20 publications in top journals and conferences. He is an NVIDIA DLI-certified instructor in Natural Language Processing and Computer Vision. Education: Ph.D. (Computer Science, NTUA), Diploma in Chemical Engineering (NTUA), M.Sc. in Techno-Economic Systems (NTUA) Research interests span health informatics, wearable devices, and sensor fusion, with projects in biomedical signal analysis and IoT applications. His work includes developing radar-based systems for health monitoring and AR/VR solutions for rehabilitation. He actively participates in EU-funded projects and promotes trustworthiness in social media through initiatives like EUNOMIA. Recent publications emphasize health tech innovations, such as stress detection via PPG signals, UWB radar-based human detection, and multimodal fusion for 3D pose estimation. His contributions also address cultural heritage preservation through VR and crowdsourcing. Grants and collaborations involve European R&D projects in IoT security, emergency response systems, and decentralized social media frameworks. He leads efforts in embodied AR for medical applications and energy-efficient neural networks.
Dimitris Kalogeras is a Researcher at the National Technical University of Athens (NTUA) , affiliated with the School of Electrical and Computer Engineering and the EPISEY research institute. He has been a key contributor to advanced networking initiatives, including the NTUA Network, EDET optical network, and University School Network. His work spans national and European projects like GEANT, 6net, and NOVI, and he pioneered IPv6 and multicast deployment in Greece and Europe. His research focuses on Network security Internet of Things (IoT) Artificial intelligence in networking Cyber-physical systems Robotics Medical image processing Recent work involves federated learning, UAV-based localization, and privacy-preserving frameworks in IoT environments. An analysis of his 15 most recent publications reveals strong emphasis on applications of machine learning in network security, robotic infrastructure maintenance, and lightweight AI for IoT. His projects include thethingsNetwork deployment in Athens, the HERON robotic platform, and the FELICE collaboration framework. He has contributed to global IoT initiatives through multi-channel LoRAWAN gateways and 6LowPAN mesh networks. His work on blockchain-based DDoS mitigation and semantic-aware policy management demonstrates leadership in cyber infrastructure resilience.
George Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He is a member of the IPAN lab and serves as a Guest Editor for a special issue on 'Entropy in Biomedical Engineering' in the journal Entropy . His research bridges biomedical engineering and computational systems, with a strong focus on entropy-based methods and machine learning for physiological signal analysis. PhD in Computer Science, National Technical University of Athens (1993–1997) MSc in Advanced Methods in Computer Science, Queen Mary, University of London (1992–1993) Diploma in Electrical and Computer Engineering, National Technical University of Athens (1987–1992) His primary research interests include Biomedical Engineering , Entropy Analysis (especially Bubble Entropy), Fast Computation Algorithms , Biomedical Data Classification , Heart Rate Analysis , and Computing Systems with emphasis on parallelization. He teaches postgraduate courses in data analysis and biomedical data processing, and undergraduate courses in compilers. The analysis of his recent publications reveals a consistent trend in developing computationally efficient and robust methods for entropy estimation and classification in biomedical contexts. His work on Bubble Entropy eliminates the need for scale parameters and enhances stability, while his improvements to Random Forests and Support Vector Machines target enhanced diagnostic accuracy in diseases like Alzheimer’s and heart conditions. In computing systems, he has pioneered compiler technologies for parallelizing recursive functions and optimizing runtime scheduling. No scientific awards are explicitly mentioned in the provided text. George Manis has advised or collaborated with several researchers, including Evanthia Tripoliti, Dimitrios Fotiadis, Petros Arsenos, Argyro Kampouraki, and others, indicating active supervision and research leadership. He is currently involved in funded projects such as Palimpsest , an interactive museum system, and Homore , a smart monitoring system for elderly individuals. These projects reflect his interest in applying advanced computing to real-world biomedical and societal challenges. He is affiliated with the IPAN lab and contributes to the development of innovative algorithms for entropy computation and parallel processing. His work on the C2μTC/SL compiler and Ariadne system demonstrates deep expertise in compiler design for specialized architectures like the SVP processor.
Yiannis Dendramis is an Associate Professor in the Department of Economics at the Athens University of Economics and Business (AUEB), within the School of Economic Sciences. He has previously held academic positions as a Marie Skłodowska-Curie European Research Fellow, Lecturer at the University of Cyprus, and Lecturer and Research Fellow at Queen Mary University of London, reflecting a strong international academic profile. His research centers on Financial Econometrics , with emphasis on applied and theoretical modeling of high-dimensional data and the integration of machine learning methods into econometric frameworks. His work spans applications in finance and macroeconomics, particularly in forecasting, risk modeling, and policy evaluation. The analysis of his recent publications reveals a consistent focus on modern econometric techniques, including penalized regression, factor models, and machine learning algorithms applied to financial and macroeconomic datasets. His research contributes to both methodological advancements and empirical insights in areas such as volatility forecasting, systemic risk, and energy policy. He has published in leading journals including Econometric Theory , Journal of Banking and Finance , International Journal of Forecasting , and Energy Policy . While no specific scientific awards are mentioned in the provided text, his publication record indicates significant scholarly impact. Dendramis advises graduate students in econometrics and economics, though specific names are not listed. His research likely involves collaborations and access to institutional data resources, but no formal grants or funding programs are explicitly mentioned. He does not appear to lead a named research lab or team based on the available content.
Gunopulos Dimitrios is a Professor at the National and Kapodistrian University of Athens, Department of Informatics and Telecommunications. His research focuses on data science, machine learning, mobility data analysis, and interdisciplinary applications in urban systems, finance, and high-energy physics. He has contributed to frameworks like INSIGHT for urban traffic management and REMI for heterogeneous data mining. His work spans cloud computing, explainable AI, and spatiotemporal analysis, addressing challenges in real-world systems. Education: Education details not explicitly provided in the text. Research Interests: Dimitrios explores cutting-edge topics such as mobility data science, serverless computing, deep learning for financial forecasting, and causal reasoning. His work bridges theoretical computer science with practical applications in urban infrastructure, healthcare, and sensor networks. Recent efforts include developing algorithms for sparse data handling, fault detection in traffic systems, and counterfactual explainability in AI. Awards: No scientific awards explicitly mentioned in the text. Advising & Grants: No listed advisees or grant details available. His contributions are primarily through collaborative frameworks and conference engagements. Labs/Teams: Involved in projects like INSIGHT for urban data integration and Dione for big data application profiling. Collaborates on heterogeneous data analysis and cloud resource optimization initiatives.
