Find Academic Supervisors

• Data Science
• Data Mining
• Big Data Analytics
• +8 more

Nikolaos Pelekis is a Professor at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus, where he teaches courses in Data Science, Data Management, Information Systems, and Computer Programming. He has been actively involved in both undergraduate and postgraduate education, offering specialized courses such as "Statistical Data Mining Methods" in the Applied Statistics Master's program and "Big Data Management" in the Cybersecurity and Data Science postgraduate program. Born in 1975, Professor Pelekis earned his Bachelor's degree in Computer Science from the University of Crete (1998), followed by an MSc in Information Systems Engineering (1999) and a PhD in Moving Object Databases (2002) from UMIST University in the United Kingdom. His educational background laid the foundation for his distinguished career in data science and database management. Professor Pelekis' research spans multiple domains within data science and database management, with particular emphasis on mobility data analytics. His work focuses on data mining, big data management and analytics, with special attention to location and motion data including trajectories of moving objects. He has made significant contributions to spatial and spatiotemporal database management, moving object database systems, privacy-preserving data mining, and OLAP analysis. His research bridges theoretical foundations with practical applications, particularly in maritime and transportation domains. An analysis of Professor Pelekis' recent publications reveals a strong trend toward maritime data analytics and vessel traffic prediction. His work increasingly focuses on applying machine learning techniques to maritime trajectory data, developing systems for collision risk assessment, vessel location forecasting, and maritime route prediction. The research demonstrates a progression from foundational database management techniques to sophisticated analytics for time-critical mobility forecasting, with applications in aviation and maritime domains. Five best research paper awards 1st & 3rd place in the SemEval-2017 competition 3rd place in the ACM SIGSPATIAL Cup 2016 competition Best paper award at ACM SIGSPATIAL'14 (Path-based Queries on Trajectory Data) Best paper award at ER'13 (Baquara: A Holistic Ontological Framework for Movement Analysis with Linked Data) Best application paper award at ICDM'09 (Clustering Trajectories of Moving Objects in an Uncertain World) Ralf H. Güting best research paper award at SSTD'21 (A Novel Indexing Method for Spatial-Keyword Range Queries) Best Demo Paper award at SSTD'21 (MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories) Professor Pelekis has been actively involved in advising and research funding acquisition. He has participated in over 10 European and National Research and Development projects as principal investigator or key researcher. His leadership extends to directing research laboratories and coordinating large-scale collaborative projects. As co-founder of the Data Science Lab - DataStories at the University of Piraeus, he has mentored numerous researchers and students. His research has been supported by prestigious funding programs including Horizon Europe, Horizon 2020, and national research initiatives. Professor Pelekis co-founded and leads the Data Science Lab - DataStories at the University of Piraeus, which comprises 9 faculty members from 4 different Departments along with experienced and young researchers. He previously served as Head of Research for the Information Management Lab (InfoLab) at the Department of Informatics, University of Piraeus (2005-2014). His current research team is actively engaged in multiple European projects including "DAT.AI – Energy-efficient AI-ready Data Spaces" and "EMERALDS – Extreme-scale Urban Mobility Data Analytics as a Service," focusing on cutting-edge applications of data science in maritime and urban mobility contexts.

Georgios KargasView profile

Professor

• Soil Physics
• Irrigation Engineering
• Hydrodynamics of Porous Media
• +4 more

Georgios Kargas serves as a Professor in the Department of Water Resources Management within the School of Environment and Agricultural Engineering at the Agricultural University of Athens (AUA). His academic profile centers on advanced irrigation engineering, soil physics, and hydrodynamics of porous media, with particular expertise in drainage system design, soil salinity assessment, and sensor-based soil moisture monitoring. His research interests focus on hydrodynamic characteristics of porous media , precision irrigation systems , and soil-water-electrical conductivity relationships . Current work emphasizes developing novel infiltration equations for furrow irrigation, validating low-cost sensor platforms for soil monitoring, and creating EU-wide soil salinity mapping frameworks using machine learning. His experimental approach bridges laboratory measurements with field applications, particularly in Mediterranean agricultural contexts. Analysis of his 15 most recent publications (2023-2025) reveals dominant trends in sensor technology validation (TEROS/WET sensors), advanced infiltration modeling consistent with Philip theory, and large-scale soil salinity mapping using EU databases. Key subfields include subsurface drainage equation development, LoRa-based monitoring systems, and electrical conductivity compensation methods for dielectric sensors. Professional contributions include editorial review work for Sensors (2021), Water (2016), and Sustainability (2017) journals, though no specific scientific awards are documented in available sources. Teaching responsibilities encompass core undergraduate and postgraduate courses including Hydrodynamic Characteristics of Porous Media , Special Topics in Soil Physics , and Irrigation-Drainage Systems Design , with consistent focus on Water Resources Management specialization. His instructional approach integrates theoretical principles with practical system design applications across 8th-9th semester curricula.

Karakassis IoannisView profile

Professor

• Marine Ecology
• Biodiversity Conservation
• Coastal Ecosystem Dynamics
• +3 more

Ioannis Karakassis is a Professor at the University of Crete's Department of Biotechnology and Applied Biology, serving as Director of Sector C (Biotechnology) from 2023-2025. He holds a PhD in Biology from the University of Crete (1991). His research focuses on marine ecology, coastal ecosystem dynamics, and the environmental impacts of aquaculture. His work emphasizes biodiversity conservation, trace element cycling, and sustainable aquaculture practices, with a particular interest in seagrass ecosystems and benthic-pelagic coupling. Key contributions include the development of the EURO-CARBON database for European sediment organic carbon, studies on microplastic contamination in shellfish, and assessments of aquaculture's ecological footprint. His recent publications address bioremediation roles of holothurians, climate change impacts on marine organisms, and spatial management strategies for Mediterranean fisheries. He has led projects on benthic macrofauna biodiversity (MacroBen database), aquaculture zoning (Allocated Zones for Aquaculture), and ecosystem-based management. His work bridges ecological research with policy, advocating for sustainable seafood production and marine spatial planning.

Theodoridis IoannisView profile

Professor

• Data Science
• Databases
• Big Data Management
• +3 more

Professor Theodoridis Ioannis is a distinguished faculty member in the Department of Informatics at the University of Piraeus, where he serves as Director of the Data Science Laboratory within the School of Information and Communication Technologies. With a career spanning over two decades, he has established himself as a leading expert in data management and analysis. His research interests focus on Data Science, particularly in databases, big data management, data mining, and geoinformatics. Professor Theodoridis has made significant contributions to spatial database systems, time series analysis, and distributed data processing. His work bridges theoretical foundations with practical applications in areas such as smart cities, mobility analytics, and scientific data management. His publication record demonstrates consistent research productivity with over 100 peer-reviewed articles in top-tier venues, accumulating more than 10,000 citations. His research output shows a clear evolution from foundational database techniques toward contemporary challenges in big data analytics, machine learning integration, and privacy-preserving methods. Member of editorial board of ACM Computing Surveys (since 2016) Reviewer for numerous international journals and conferences Active participant in data management conference committees Professor Theodoridis has secured significant research funding through Horizon 2020 projects, serving as project coordinator and research team leader since 2001. His work demonstrates strong industry and academic collaboration, with applications spanning multiple domains. He has also co-authored three influential monographs in his field. He leads the Data Science Laboratory, which serves as a hub for interdisciplinary research at the intersection of database systems, machine learning, and domain-specific applications. The laboratory fosters collaboration between computer scientists, domain experts, and industry partners to address real-world data challenges.

• Data Mining
• Machine Learning
• Graph Mining
• +9 more

Michalis Vazirgiannis is a Professor in the Department of Informatics at the Athens University of Economics and Business (AUEB), specializing in data mining and machine learning with applications in web and social network analysis. His work bridges theoretical algorithms and real-world scalability challenges. Education: Bachelor Degree in Informatics, National and Kapodistrian University of Athens, 1986 Master (M.Sc.) in Robotics, National and Kapodistrian University of Athens, 1988 Master (M.Sc.) in Knowledge Based Systems, Heriot Watt University, Edinburgh, 1989 Ph.D. in Informatics, National and Kapodistrian University of Athens, 1994 Research Focus: Professor Vazirgiannis pioneers clustering algorithms with subjective/objective validation, distributed feature selection for evolving graphs, and temporal link analysis for dynamic page ranking. His research addresses critical gaps in semi-supervised learning for large-scale web and social networks, emphasizing dimensionality reduction and ranking predictability in temporal contexts. Publication Trends: His 2007-dominated publications reveal a strategic shift toward graph-based web mining, with recurring themes of distributed processing (P2P similarity search), clustering validity frameworks, and semantic web personalization. The work consistently targets scalability bottlenecks in real-world network data. Scientific Recognition: ERCIM Post-doctoral Scholarship (2001) Marie Curie European Scholarship (2006) Leadership & Collaboration: As ERASMUS coordinator for AUEB's Informatics Department and editorial board member of Intelligent Data Analysis journal, he bridges academia and industry. His EU project leadership (FP6 SQO-OSS, Marie Curie NGWeMiS) and program committee roles (IEEE/ICDM 2008, ECML/PKDD 2008) highlight his influence in data mining standardization. International collaborations span INRIA, Fraunhofer, Max Planck, and IBM Research. Technical Innovation: His patent contributions and invited lectures at ECML/PKDD 2006/SIAM/SDM 2006 demonstrate applied impact, particularly in web personalization engines (SEWeP) and evolving graph analytics.

Papadopoulos ApostolosView profile

Associate Professor

• Databases
• Data Mining
• Spatial Databases
• +7 more

Apostolos Papadopoulos is an Associate Professor at the Department of Informatics , Aristotle University of Thessaloniki , Greece. His research focuses on databases, data mining, and big data analytics. Born in Eleftheroupolis, Greece Diploma in Computer Engineering and Informatics (University of Patras) PhD in Informatics (Aristotle University of Thessaloniki) Research Interests: Spanning DATABASES and DATA MINING , his work includes: Efficient query processing in multidimensional and spatio-temporal databases Graph mining algorithms (dense subgraphs, frequent patterns, probabilistic graphs) Parallel/distributed systems (Spark, Hadoop) for massive datasets Real-time data stream analysis Scientific Recognition: Best Paper at EDBT 2014 (selected for ACM Transactions on Database Systems) Best Knowledge Discovery Paper at ECML/PKDD 2008 Google Scholar h-index: 25 PhD Supervision: Mentoring 4 ongoing PhD students and one graduated candidate (Eleftherios Tiakas).

• Computer Vision
• Neural Networks
• Pattern Recognition
• +3 more

Nikolaos Vassilas serves as Professor in the Department of Informatics and Computer Engineering at the University of West Attica, Greece, with leadership roles including Director of the Intelligent Knowledge, Image & Information Systems research Laboratory (ISLab) since 2019 and former Director of the Joint Greek-French Master Degree Program (2016-2020). His academic journey includes research positions at NCSR "Demokritos" and EPFL. His educational credentials feature a Diploma in Electrical Engineering from Aristotle University of Thessaloniki (1983), and M.S.E.E. and Ph.D. degrees from the University of Minnesota (1987, 1990). Professional affiliations include IEEE Computational Intelligence Society, Hellenic Society of Artificial Intelligence, and Greek Computer Society. Professor Vassilas' research centers on Computer Vision and Neural Networks with applications in urban analysis and remote sensing. His work integrates deep learning for building extraction from aerial/LiDAR data, semantic modeling in 3D urban environments, and neural network-based environmental prediction systems. Key methodological focuses include mean-shift algorithms, Hough transforms, and multisource spatial data fusion. Analysis of his recent publications reveals consistent specialization in computer vision techniques for urban infrastructure analysis, particularly building contour detection and 3D reconstruction using convolutional neural networks. The integration of aerial imagery with elevation data and robust line detection algorithms represents a dominant research trajectory across his 70+ publications. No scientific awards were documented in the source materials. He has coordinated two European Union co-funded research programs and participated in multiple national projects, with expertise in environmental data processing and intelligent spatial analysis systems. His leadership extends to directing research laboratories and international academic programs, demonstrating significant grant management experience. Professor Vassilas leads the Intelligent Knowledge, Image & Information Systems research Laboratory (ISLab), which focuses on advancing computer vision techniques for urban planning and environmental monitoring applications through interdisciplinary team collaboration.

Antigoni TsiamiView profile

Research Fellow

• Multimodal Signal Processing
• Robotics
• Speech Enhancement
• +7 more

Antigoni Tsiami is a Postdoctoral Research Associate at the National Technical University of Athens (NTUA), affiliated with the School of Electrical and Computer Engineering (ECE) and the CVSP Group. She has been a PhD student since 2013, focusing on audio and speech processing applications. Her work spans robotics, signal processing, and assistive technologies. Education: Diploma in Electrical and Computer Engineering from NTUA (2012) PhD candidate in the CVSP Group, ECE School, NTUA under Prof. Petros Maragos Research interests: Multichannel speech enhancement and acoustic source localization Audiovisual scene perception for human-robot interaction Far-field processing techniques MEMS microphone applications Multimodal perception systems for assistive robotics Home automation control via spoken commands Her research projects include BabyRobot and COGNIMUSE , exploring multimodal signal processing in cognitive robotics and human interaction scenarios. Recent publications demonstrate focus on integrating sensory data for practical robotics applications, emphasizing robustness in real-world environments. She collaborates with interdisciplinary teams including the CVSP Group and EU-funded initiatives. Advising/Grants: While no advisees are listed, her current postdoctoral role suggests ongoing research collaborations. She participates in grant-funded projects such as BabyRobot and COGNIMUSE. Labs/Teams: Active member of the CVSP Group and contributed to the IROS 2015 workshop on Cognitive Mobility Assistance Robots. Engaged with multidisciplinary teams in EU robotics initiatives.

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Constraint Satisfaction
• +9 more

Koumbarakis Manolis is a Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, serving since April 2011. His prior positions include Associate Professor at the same university (2005–2011), Assistant/Associate Professor at the Technical University of Crete (1999–2005), Lecturer at the University of Manchester (1995–1998), and Research Associate at Imperial College London (1993–1995). Education: PhD in Computer Science (1994), National and Kapodistrian University of Athens MSc in Computer Science (1988), University of Toronto BA in Mathematics (1986), University of Crete Research Interests: His work spans artificial intelligence (knowledge representation, reasoning, constraint satisfaction), distributed systems (P2P networks, cloud computing), web technologies (semantic web, information retrieval, web services), and databases (temporal, spatial, and constraint databases). Teaching: He instructs courses including Artificial Intelligence I, Artificial Intelligence II (focused on Deep Machine Learning for NLP), and Data Structures and Programming Techniques.

• Data Mining
• Machine Learning
• Clustering Algorithms
• +5 more

Professor Michalis Vazirgiannis is affiliated with the Informatics Department at Athens University of Economics and Business (AUEB). He holds a PhD in Informatics from the National and Kapodistrian University of Athens (1994), with prior degrees in Physics, Robotics, and Knowledge-Based Systems. His research focuses on data mining, machine learning, clustering algorithms, and web mining. He has led EU-funded projects like SQO-OSS and NGWeMiS, and contributed to initiatives like DB-GLOBE and I-KnowUMine. Awards include ERCIM Post-Doctoral Scholarship (2001) and Marie Curie Fellowship (2006). He serves on editorial boards (e.g., IDA Journal) and program committees for conferences like IEEE/ICDM and ECML/PKDD. His work spans theoretical advancements and practical applications in distributed systems, semantic networks, and temporal graph analysis. Education: BSc Physics, NKUA (1986) MSc Robotics, NKUA (1988) MSc Knowledge-Based Systems, Heriot-Watt University (1989) PhD Informatics, NKUA (1994) Research interests include semi-supervised learning, page ranking, and distributed feature selection. His publications address clustering frameworks, peer-to-peer systems, and normalized PageRank for evolving graphs. He has contributed to patents and held visiting researcher positions at INRIA, Fraunhofer, Max Planck, and IBM India.

• Computer Graphics
• CAD Systems
• Geometric Modeling
• +2 more

Ioannis Fudos is Professor and former Chair (2014-2018) of the Computer Science and Engineering Department at the University of Ioannina. He holds a Diploma in Computer Engineering from University of Patras, and MS/PhD degrees in Computer Science from Purdue University. His research spans computer graphics, CAD systems, geometric modeling, animation, and image retrieval. He directs the Computer Graphics Research Group and has secured substantial funding (€2M+) from European and national sources for 17+ projects. His scholarly contributions include publications in top venues (SIGGRAPH, Eurographics, IEEE TVCG) covering rendering techniques, 3D printing quality control, assistive technologies, and cultural heritage digitization. Recent work explores neural rendering transparency methods, wheelchair navigation interfaces, and pedestrian routing algorithms. His laboratory maintains a repository of 3D models for research use.

David PetrosyanView profile

Researcher

• Quantum Optics
• Quantum Information
• Quantum Simulations
• +5 more

Dr. David Petrosyan is a Research Director at the Institute of Electronic Structure and Laser (IESL) of the Foundation for Research and Technology - Hellas (FORTH), Greece. He holds a PhD in Laser Physics from the Armenian National Academy of Sciences and has held research fellowships at institutions including the Max Planck Institute, Weizmann Institute, and Aarhus University. His work focuses on theoretical quantum optics, quantum information, and quantum simulations with cold atoms and Rydberg systems. Education: 1995: Diploma in Physics, Yerevan State University, Armenia 1999: PhD in Laser Physics, Institute for Physical Research, Armenia Research Interests: Quantum non-linear optics, spin lattice models in optical lattices, Rydberg atom interactions, quantum simulations of many-body systems, and quantum information processing using hybrid systems. His contributions include foundational work on quantum gates with Rydberg atoms and microwave-to-optical photon conversion. Awards: 2014: Friedrich W. Bessel Research Award 2013: Dale T. Mortensen Senior Fellowship 2006: Alexander von Humboldt Research Fellowship 2000: Feinberg Postdoctoral Fellowship His research groups have pioneered theoretical frameworks for quantum technologies, including photonic-crystal-based quantum computing and Rydberg-based quantum simulations. He has authored over 80 publications and a textbook on quantum optics.

• Geostatistics
• Hydrogeology
• Environmental Sustainability
• +3 more

Varouchakis Emmanouil is an Assistant Professor at the Technical University of Crete (TUC), affiliated with the School of Mineral Resources Engineering (MRE). His research focuses on geostatistical modeling, hydrogeology, and sustainable resource management. He actively contributes to projects like the IMMERSE initiative, which develops virtual excursions for critical raw materials education in the clean energy transition. His work integrates advanced statistical methods with environmental systems analysis. Key areas of expertise include groundwater dynamics, stochastic simulations for mining emissions reduction, and renewable energy potential assessment in the Mediterranean. He has developed decision support frameworks for water allocation optimization and circular economy strategies in mining waste management. His research often combines geostatistics with machine learning and remote sensing data to enhance environmental monitoring and predictive modeling. Emmanouil collaborates on EU-funded initiatives such as the OurMED project for sustainable water storage and the InTheMED project analyzing groundwater dynamics. He has authored numerous papers on topics like space-time correlations in mineral dissolution, spatial variability of precipitation, and probabilistic forecasting of extreme climate events. His academic contributions span both theoretical advancements (e.g., covariance models in multivariate geostatistics) and applied solutions (e.g., wave energy assessments in the Aegean Sea). He maintains an active role in advancing methodologies for climate resilience in energy infrastructure and groundwater resource management systems.

Andreas GöbelView profile

Professor

• Computational Counting
• Randomness in Computation
• Computational Complexity
• +4 more

Andreas Göbel is a Professor and Chair of Algorithm Engineering at the Hasso Plattner Institute (HPI). His research focuses on computational counting, randomness in computation, computational complexity, graph theory, and stochastic processes. He has contributed extensively to understanding diffusion processes, clique structures in networks, and algorithmic approaches to statistical physics problems. His work bridges theoretical computer science with practical algorithm design. Recent contributions include analyzing SIRS process survival times, clique dynamics in geometric random graphs, and non-linear information diffusion models. He has published widely in top-tier conferences such as IJCAI, AAAI, and SODA. Göbel teaches courses including Probability and Computing, Algorithmix, and Theoretical Foundations of Cryptography. His research group explores both foundational aspects of algorithms and real-world applications, particularly in network science and combinatorial optimization.

Emiris IoannisView profile

Professor

• Computer Algebra
• Computational Geometry
• Computer-Aided Geometric Design
• +9 more

Emiris Ioannis is a Professor in the Department of Informatics & Telecommunications at the University of Athens. He holds a BScEng from Princeton University, MSc and PhD from UC Berkeley, and a Habilitation from the University of Nice Sophia Antipolis. His research focuses on computer algebra, computational geometry, robotics, bioinformatics, and fairness in AI. He has held tenured positions at INRIA, France, and has collaborated with institutions like ENS-Ulm, IHES, and the Ontario Research Center for Computer Algebra. His work bridges theoretical and applied areas, including structural bioinformatics, algorithm development, and machine learning. Notable contributions include tools for protein structure analysis (e.g., Hydraprot), explainable AI frameworks (GLANCE), and predictive models for renewable energy (wind speed forecasting). His research often intersects with interdisciplinary challenges in robotics, finance, and environmental sustainability. Emiris has organized international workshops and contributed to conferences like ISSAC. His publications span high-impact journals in computer science, mathematics, and bioinformatics. Despite no explicitly listed awards, his extensive academic contributions and leadership roles reflect his impact in theoretical informatics. His advising and grants focus on collaborative projects involving geometric algorithms, AI ethics, and data-driven decision systems. Research teams under his leadership often involve cross-disciplinary collaborations, addressing both fundamental and applied problems in computational science.