Find Academic Supervisors

Christos BerberidisView profile

Research Fellow

• Machine Learning
• Data Mining
• Natural Language Processing
• +4 more

Dr. Christos Berberidis is a Research Fellow and Faculty Member at the International Hellenic University, where he coordinates activities within the DORG Research Group. His academic foundation includes a BSc in Informatics from Aristotle University of Thessaloniki (1998), an MSc in Information Systems Engineering from the University of Manchester (1999), and a PhD from Aristotle University's Department of Informatics. Research Focus Dr. Berberidis specializes in interdisciplinary domains at the intersection of computer science and real-world applications: Core methodologies : Machine Learning, Data Mining, Natural Language Processing, and Deep Learning Applied research : Disinformation analysis, fake news detection, semantic web technologies, and bioinformatics Emerging domains : Digital governance transformation and ethical AI frameworks Publication Trends His scholarly output demonstrates evolving focus areas: early work centered on bioinformatics and transaction database mining (2005-2013), shifting toward semantic web applications (2010-2013), and currently emphasizing disinformation analysis, digital government, and AI ethics (2021-present). Methodological consistency in machine learning underpins all research phases. Professional Activities Former Visiting Researcher at Purdue University's Department of Computer Sciences Adjunct Lecturer at Aristotle University teaching programming methodologies Research consultant and project manager for private sector R&D initiatives Active contributor to EU projects including JustReDi (regional digital transition) and digiGOV-innoHUB (digital skills development) Team Affiliations Dr. Berberidis coordinates research at the DORG Group, focusing on data-centric governance, AI applications, and digital innovation within the International Hellenic University ecosystem.

Konstantinos KotisView profile

Associate Professor

• Knowledge Engineering
• Semantic Web
• Internet of Things (IoT)
• +7 more

Konstantinos Kotis is an Associate Professor and Team Leader at the Department of Cultural Technology and Communication, University of the Aegean, and a Research Associate at the AI Lab of the University of Piraeus. He leads the Semantic Web of Things group and directs the Postgraduate Studies in Cultural Informatics. Kotis has held roles including IT Manager at regional governmental bodies (2000–2018) and committee member for entry-level exams and procurement since 2019. He is also Deputy Manager for student placements in industry and government sectors. Education: BSc in Computation from the University of Manchester, UK, and PhD in Information Management (Knowledge Representation/Management) from the University of the Aegean, Greece. Postdoctoral roles include positions at the University of the Aegean’s AI Lab (2010–2015), VTT Technical Research Centre of Finland as an ERCIM fellow (2011–2012), and the University of Piraeus’s AI Lab (2013–2018). Research interests span Knowledge Engineering , Semantic Web technologies , Semantic Data Management , and IoT . He focuses on ontology development for domains like healthcare (e.g., Wear4PDmoveOnto for PD patient monitoring), cybersecurity in IoT (IoT Trust Ontology), and semantic integration of cultural heritage data. Kotis has authored over 100 peer-reviewed publications (h-index 21) and contributed to projects such as Grid4All (FP7, 2008), iCore (FP7, 2012), and Time Machine (H2020, 2019). Scientific awards include the ERCIM ‘Allain Bensoussan’ post-doctoral fellowship (2011–2012). His work bridges academic research and practical applications, emphasizing semantic interoperability, fairness in AI, and ontology-driven decision support systems. He actively supervises graduate/postgraduate research and collaborates on ontology frameworks like the Semantic Social Network of Things.

Michalis FeidakisView profile

Lecturer

• Affective Computing
• Distance Learning
• Robotics
• +3 more

Mitchalis Feidakis is a Lecturer in the Department of Electrical & Electronics Engineering at the University of West Attica (UNIWA) , and a Senior Researcher at the UNIWA CoNSeRT Lab. He also serves as a member of the Open University of Catalonia's SMARTLEARN Research Group. His academic background includes a Ph.D. in Affective Computing & Learning (University of Aegean), an MSc in Multimedia and Internet Computing (Loughborough University, UK), and a BSc in Informatics (Athens University of Economics). Feidakis has over 15 years of experience coordinating National, EU, and Asian-European Network (AEC-Net) projects . His research focuses on Affective Computing with applications in Distance Learning , Robotics , and Computer-Supported Collaborative Learning (CSCL) . He has published extensively in top-tier journals and conferences, and his work has been recognized with 2 gold and 1 merit awards from the AEC-Net Project (2006, 2009, 2012). In addition to his academic roles, he has served as an ICT Teacher across all education levels (Primary, Secondary, Vocational, Adult), and held advisory roles such as National Coordinator of AEC-Net and Assistant to the Secretary General at the Ministry of Education's Information Society Office (2004–2008). His teaching includes courses like Wearable and Affective Computing . Feidakis' research interests span Emotional AI systems , Human-Robot Interaction , and Smart Infrastructure Security . He actively contributes to interdisciplinary projects, including the DESOS Project for intelligent security systems and the NAO robot-based educational interventions for students with Autism Spectrum Disorder.

Georgios PatrikiosView profile

Research Fellow

• Open Data
• Linked Data
• Semantic Web
• +8 more

Georgios Patrikios serves as a Postgraduate Research Fellow at the DORG Research Group, International Hellenic University, specializing in data science research with cross-disciplinary applications. His academic credentials include: Bachelor of Business Administration from the University of Macedonia Master of Data Science from the International Hellenic University Research integrates Data Mining, Natural Language Processing, and Semantic Web technologies with practical implementations in Business Intelligence and legal document analysis. Key methodological strengths encompass Linked Data frameworks, Ontology Engineering, and Graph Mining for complex data systems. Active projects demonstrate applied research impact: R&D in Semantic Interoperability: Machine learning and NLP systems extracting organizational structures from legal documents Feasibility Studies: Sub-contracted comparative analyses for ICON-INSTITUT Public Sector Gmbh As a core DORG Research Group member, he contributes to open data initiatives while advancing visualization techniques for business intelligence applications.

Doulkeridis ChristosView profile

Professor

• Big Data
• Data Management in Cloud Computing
• Query Processing
• +5 more

Christos Doulkeridis is a Professor at the Department of Digital Systems, University of Piraeus. Specializing in big data management, distributed systems, and mobility analytics, he has led projects such as CHOROLOGOS (ELIDEK-funded) and contributed to EU initiatives like datAcron and Track&Know. He holds Marie-Curie and ERCIM fellowships, and his work emphasizes energy-efficient data architectures and semantic trajectory analysis. Education: PhD in Informatics, Athens University of Economics and Business (2007) MSc in Informatics, Athens University of Economics and Business (2003) Diploma in Electrical & Computer Engineering, National Technical University of Athens (2001) Research Interests: Big data analytics, cloud computing, spatiotemporal query processing, mobility forecasting (e.g., traffic patterns, maritime monitoring), and semantic trajectory modeling. His work bridges theory with practical applications in smart cities and environmental sustainability. Awards: Winner of SemEval’17 Task4 (sentiment analysis) Best Paper Award at EuroVA’19 Michalis Dertouzos Award (2004) for Human Face of Computing Grants & Projects: Principal Investigator for CHOROLOGOS (semantic spatiotemporal data) Core contributor to datAcron (maritime data ontology) European projects: BigDataStack, RoadRunner (ARISTEIA II) Labs & Teams: Leads research teams developing frameworks like SPARTAN (semantic integration) and ARGO (trajectory prediction). Collaborates on open-source tools like ST_VISIONS (spatiotemporal visualization) and NoDA (unified NoSQL access).

Christos NomikosView profile

Associate Professor

• Algorithm Design and Analysis
• Approximation Algorithms
• Computational Complexity
• +3 more

Christos Nomikos is an Associate Professor at the Department of Computer Science and Engineering, University of Ioannina. He holds a PhD from the National Technical University of Athens (NTUA) and has been a faculty member since 2003. His roles include teaching and research supervision in computer science disciplines. Education: Diploma in Electrical Engineering, NTUA, 1992 PhD in Computer Science, NTUA, 1997 Research Interests: Christos Nomikos focuses on theoretical computer science and logic, including algorithm design and analysis, computational complexity, formal languages, logic programming, and graph theory. His work explores foundational aspects of programming languages and their semantics, as well as applications in knowledge representation and automated reasoning. Teaching: In the 2024-25 academic year, he teaches Discrete Mathematics II , Principles of Programming Languages , Computational Complexity , and Approximation Algorithms . He emphasizes structured learning approaches and maintains a dedicated ecourse page for students. Advising & Grants: He supervises undergraduate thesis projects in computer science, with a focus on theoretical topics like Turing machine transformations and Boolean grammar algorithms. No explicit grant information is provided in the texts. His advising process involves rigorous academic evaluation and prefers candidates with strong performance in core computer science courses. Labs/Teams: While no specific lab or team affiliations are mentioned, his research collaborations include work with international conferences and journals, indicating active participation in academic networks.

• Artificial Intelligence
• Automated Planning
• Machine Learning
• +7 more

Dimitris Vrakas is an Assistant Professor at the Department of Informatics, School of Informatics, Aristotle University of Thessaloniki (AUTh). He holds a PhD in Intelligent Planning Systems and has conducted post-doctoral research focusing on Planning for the Semantic Web. His professional experience includes roles as a Lecturer (per Greek law 407/80), Informatics Instructor in multiple educational institutions, and IT consultant for medium-sized enterprises through the Go-online Project. Education: Bachelor of Science (1995–1999): Informatics, Aristotle University of Thessaloniki PhD (2000–2004): Intelligent Planning Systems, Dept. of Informatics, AUTh Postdoctoral Research (2005–2007): Planning for the Semantic Web, AUTh Research Interests: Automated Planning, Heuristic Functions, Intelligent Autonomous Systems, Machine Learning Applications (Energy Management, NILM), Semantic Web Services, and Smart Environment Technologies. His work bridges theoretical AI advancements with practical implementations in energy systems and emergency response. Publications: Over 45 papers (including 15 journal articles) and 5 book chapters, with a focus on energy disaggregation, evacuation algorithms, and semantic web composition. His work demonstrates expertise in applying advanced techniques like GANs for data generation and reinforcement learning for adaptive planning. Awards: 2025 ACM SIGMOD Test-of-Time Award for contributions to time-series clustering Advising & Grants: Active in guiding PhD candidates (as per recent calls) and coordinating projects like the IRIS RISK PARADIGM for industrial safety. His work involves developing smart university platforms for energy monitoring and collaborating on EU-funded initiatives. Labs & Teams: Member of the Intelligent Systems Lab at AUTh, contributing to projects like the BOnSAI ontology for smart buildings and the IRISPortal for risk management. He also coordinates the Hellenic Artificial Intelligence Society and chairs conferences like SETN 2016.

Theodosiadou OuraniaView profile

Researcher

• Stochastic modeling
• Time series analysis
• Applied probabilities
• +3 more

Ourania Theodosiadou is a Researcher at the Department of Mathematics, Aristotle University of Thessaloniki (since Oct 2024). Previously, she served as a Postdoctoral Researcher at the Institute of Information and Communication Technologies (CERTH) from 2019 to 2024 and held multiple contracted lecturer roles at Aristotle University and the University of Macedonia. She earned a PhD in Mathematics (2019) and a Master's in Statistics and Modeling (2014), both from AUTH, with a focus on stochastic processes and financial applications. Her doctoral thesis explored latent stochastic processes with jumps in finance under Prof. Georgios Tsaklidis. Her research interests span stochastic modeling, time series analysis, computational statistics, and machine learning. Recent work includes real-time threat assessment using Hidden Markov Models (2023), cryptocurrency transaction analysis for illegal activity detection (2023), and centrality-based network node identification (2022). Methodological contributions include state space modeling with constraints (2021) and Kalman filter applications for jump detection in financial markets (2017-2019). Publications reflect interdisciplinary applications in finance, security, and computational methods. Current work extends AI-driven solutions against terrorist financing and explores blockchain forensics through time series analysis.

Livieris IoannisView profile

Assistant Professor

• Machine Learning
• Optimization Methods
• Deep Learning
• +7 more

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.

George TsekourasView profile

Professor

• Artificial Intelligence
• Cultural Informatics
• Machine Learning
• +6 more

Prof. George Tsekouras is a Professor in the Department of Cultural Technology and Communication at the University of the Aegean since 2002. His research focuses on artificial intelligence, cultural informatics, and expert systems, with over 100 publications in journals and conferences. He has contributed to projects involving machine learning fairness, blockchain sustainability, healthcare monitoring systems, and cultural heritage preservation. Research interests include AI applications in cultural heritage (e.g., 3D asset quality, art recoloring for color blindness), ethical AI in criminal justice systems, energy-efficient blockchain technologies, and environmental monitoring via machine learning. His work bridges computational methods with societal challenges, emphasizing interdisciplinary approaches. Notable trends in his publications include leveraging graph neural networks for healthcare (e.g., Parkinson’s disease monitoring), exploring ChatGPT for hospitality personalization, and developing hybrid machine learning models for disaster prediction. His contributions span technical innovation and social impact, such as improving accessibility through image recoloring algorithms and reducing blockchain’s environmental footprint. No scientific awards are listed. Advising and grants details are unavailable, but his extensive publication record indicates active research collaboration. His work often integrates cultural data with computational tools, reflecting his department’s mission at the University of the Aegean.

Dimitrios MichailView profile

Associate Professor

• Algorithms
• Graph Algorithms
• Machine Learning
• +6 more

Dimitrios Michail is an Associate Professor in the Department of Computer Science and Telecommunications at Harokopio University. He holds a Diploma in Electronic Engineering and Computer Engineering from the Polytechnic University of Crete, a Master's in Computer Science, and a Ph.D. in Algorithms from the Max-Planck Institute for Computer Science. His research focuses on algorithms for modern computational models, graph algorithms, machine learning, and their applications in computer vision, wildfire prediction, and social network analytics. He has been involved in European projects like TELEIOS and DeepCube. His work intersects earth observation, autonomous systems, and AI-driven solutions for environmental challenges. Recent research includes Earth-as-a-Graph frameworks for wildfire forecasting and novel datasets for InSAR analysis. He has contributed to libraries like JGraphT and JHeaps, emphasizing algorithmic efficiency and open-source tools. Michail's publications span graph theory, deep learning, and remote sensing applications, with a focus on real-world problems like flood mapping and fake news detection. He has collaborated on projects addressing urban mobility, public transport optimization, and disaster preparedness through spatio-temporal modeling.

George P. KafentzisView profile

Lecturer

• Speech Signal Processing
• Emotion Recognition in Speech
• Deep Learning
• +5 more

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.

• Computer Science
• Data Structures and Algorithms
• Theoretical Computer Science
• +1 more

Assistant Professor at the Department of Agricultural Economics and Rural Development, Agricultural University of Athens. Holds a PhD, MSc, and BSc in Computer Engineering and Informatics from the University of Patras. Research focuses on dynamic graph problems, query optimization, and theoretical data structures with sublinear space. Teaches courses like Business Intelligence Systems and Informatics , emphasizing computer systems, databases, and data processing. His work bridges computer science theory with agricultural informatics applications. Educated at the University of Patras, he transitioned from the Department of Science (2004-2013) to his current role. Course content highlights his expertise in ETL processes, operating systems, and collaborative learning technologies.

• Deep Learning
• Multimodal AI
• Explainable AI
• +6 more

Giorgos Stamou is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), and a Visiting Professor at the MIT Sloan School of Management and MIT Open Learning. He directs the Artificial Intelligence and Machine Learning Systems Laboratory (AILS Lab) and has been a senior researcher at the Institute of Communications and Computer Systems (2000-2008) and an academic visitor at Oxford University (2011-2012). His research spans Deep Learning , Explainable AI , and Knowledge Representation , with a focus on Large Language Models and Multimodal Learning . He has coordinated over 60 funded projects and published 150+ papers. Recent work highlights trends in LLM Evaluation , Gender Bias Mitigation , and Multimodal Music Analysis , reflecting his interdisciplinary approach to AI challenges. Stamou has served on steering committees for W3C working groups (Rule Interchange Format, Web Ontology Language) and contributed to cultural heritage metadata enrichment through the CrowdHeritage projects. He founded NTUA's MSc program in Data Science and Machine Learning (2018-2022) and has organized conference tracks on riddle-solving frameworks and hallucination detection.

Chao PengView profile

Part-Time Lecturer

• Software Testing
• Program Analysis
• Programming Languages
• +5 more

Chao Peng is a Principal Research Scientist at ByteDance where he leads the Trae Research team (ByteDance Software Engineering Lab), conducting cutting-edge research on AI agents for software engineering. He also serves as a Part-time Postgraduate Student Mentor at Fudan University's School of Computer Science, bridging industry research with academic mentorship. PhD in Informatics (2021), University of Edinburgh, UK MSc in High Performance Computing and Data Science (2017), University of Edinburgh, UK BEng in Computer Science and Technology (2016), Xuzhou University of Technology, China Dr. Peng's research focuses on the intersection of software testing, program analysis, and large language models. His work explores how AI agents can revolutionize software engineering practices, with particular emphasis on automated bug detection, code generation, and testing frameworks. He has pioneered approaches for evaluating LLM performance in software engineering contexts and developing agent-based systems that enhance developer productivity while maintaining code quality and security. His recent publications demonstrate a clear trend toward integrating large language models with traditional software engineering practices. The research spans code generation evaluation, security vulnerability detection, automated bug reproduction, and issue localization. These works collectively advance the field of AI-assisted software development by addressing practical challenges in reliability, security, and efficiency of AI-generated code. Distinguished Reviewer for FSE'25 School of Informatics Scholarship (fully-funded PhD scholarship) Outstanding Graduate Scholarship at Xuzhou University of Technology Multiple China National Scholarships Honours Spot Bonus at ByteDance Certificate of Achievement for HPCAC Student Cluster Competition Dr. Peng actively mentors students through his role at Fudan University and previously at the University of Edinburgh, where he served as sub-supervisor for MSc projects and teaching assistant for software testing courses. His research has attracted significant industry attention, leading to multiple collaborations between ByteDance and academic institutions. He frequently serves on program committees for major software engineering conferences including ASE, FSE, and ICSE, demonstrating his leadership in the field. As leader of the Trae Research team at ByteDance Software Engineering Lab, Dr. Peng oversees research on AI agents for software engineering, including the application and evaluation of AI agents and training LLMs for agent-based systems. The lab's work focuses on practical systems that predict, detect, diagnose, and fix bugs across various software systems, with particular emphasis on real-world applications and measurable impact on developer productivity.