Dr. George Stamou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), serving as Director of the Artificial Intelligence and Learning Systems Laboratory (AILS). His expertise spans knowledge representation, machine learning, neural networks, and semantic technologies. He leads interdisciplinary initiatives such as the postgraduate program 'Data Science and Machine Learning' (2018–2022). Research Interests: Focuses on knowledge graphs, interpretable AI, semantic web applications, and multimodal learning. His work integrates formal logic systems (e.g., description logics) with modern deep learning techniques, addressing challenges in explainability, bias detection, and ethical AI applications. Publications: Over 150 articles in AI journals/conferences with an h-index of 34 (Google Scholar). Notable contributions include datasets like CHORDONOMICON (music analysis), GOSt-MT (gender bias in MT), and methodologies for counterfactual explanations in machine learning. Awards & Committees: Active in W3C and RuleML standardization bodies. Co-organized major AI conferences. Recognized for contributions to semantic interoperability and knowledge-based systems. Labs & Teams: Directs AILS-NTUA lab and collaborates with CISRI (Computer & Information Systems Research Institute). Engages in EU projects like CultureLabs (cultural heritage digitalization) andsmarty4covid (health data analysis).
John Psarras is a Professor at the National Technical University of Athens (NTUA) in the School of Electrical and Computer Engineering, specifically within the Division of Industrial Electric Devices and Decision Systems. He serves as the Director of the Decision Support Systems Laboratory (DSSlab) and the University Research Institute of Communication and Computer Systems. He holds a Diploma in Mechanical Engineering (1982) and a Ph.D. in Electrical and Computer Engineering (1989), both from NTUA. His research specializes in decision support systems with applications in energy management, environmental analysis, and information systems. Key areas include: Multi-criteria analysis for energy policy and renewable integration AI-driven optimization of smart grids and building efficiency Sustainable finance mechanisms for green projects Blockchain applications in education and data security His recent publications (2023–2025) demonstrate a strong focus on AI-enhanced decision tools for energy transitions, smart infrastructure, healthcare diagnostics, and cross-border renewable cooperation, reflecting interdisciplinary innovation. He has supervised 22 PhD theses and coordinates EU-funded projects in energy policy, clean technology, and capacity building. No scientific awards are listed in available sources. He leads the Decision Support Systems Laboratory (DSSlab), advancing research in energy analytics, and directs the University Research Institute of Communication and Computer Systems, facilitating large-scale interdisciplinary collaborations.
Ion Androutsopoulos is a Professor of Artificial Intelligence in the Department of Informatics at Athens University of Economics and Business (AUEB), where he also serves as Head of Department. He is founder and co-director of AUEB's Natural Language Processing Group and an Adjunct Researcher at the Digital Curation Unit and "Archimedes" Research Unit of the Research Centre "Athena". His research spans multiple dimensions of Artificial Intelligence with a focus on Natural Language Processing. Key interests include: Machine learning in NLP, particularly deep learning and large language models Question answering and retrieval augmented generation for document collections Dialog systems for new languages and knowledge domains Sentiment analysis and emotion recognition from text and speech Detecting toxic posts and disinformation online Image-to-text generation for medical diagnostics NLP applications in biomedical, legal, and financial domains His recent publications demonstrate strong activity across medical AI (particularly ImageCLEFmed Caption competitions where his group consistently ranks 1st-2nd), legal NLP (LexGLUE benchmark), financial NLP (EDGAR-CRAWLER), and multilingual challenges. His work shows increasing emphasis on large language models, explainability, and practical applications. Notable awards include: Top 2% scientist worldwide (Stanford University database, 2023) Multiple AUEB Excellent Teaching Awards (2017-18, 2021-22, 2023-24) Three consecutive BioASQ awards (2018-2020) Multiple 1st/2nd place rankings in ImageCLEFmed Caption competitions (2021-2025) He actively organizes major events including the Athens Natural Language Processing Summer School (AthNLP) and SemEval tasks. His group maintains strong industry and research collaborations, particularly in medical AI applications where they've developed systems that generate diagnostic captions from medical images with state-of-the-art performance.
Manos Kapritsos is an Associate Professor in the Department of Computer Science and Engineering at the University of Michigan's College of Engineering. He leads the GLaDOS research group focusing on reliability of distributed systems through formal verification and fault-tolerant replication techniques. His research spans: Formal verification of concurrent and distributed systems Fault-tolerant replication protocols beyond client-server models Automation of verification processes for complex systems Performance verification including latency properties Reliable cryptographic code implementation Analysis of his publications reveals strong emphasis on: developing automated verification tools (Armada, Vale, IronFleet), creating novel replication protocols (Aegean), verifying performance characteristics (Performal), and improving specification reliability (IronSpec). His work consistently bridges theoretical formal methods with practical systems implementation. Awards and honors include: Jay Lepreau Best Paper Award at OSDI 2025 Jon R. and Beverly S. Holt Award for Excellence in Teaching (2022) NSF CAREER Award (2021) Distinguished Paper Award at PLDI 2020 Google Faculty Award (2017) Distinguished Paper Award at USENIX Security 2017 Grant support includes NSF FMitF grants (2020, 2023), NSF Large grant (2021), DARPA grant (2020), and Google Faculty Award (2017). He advises PhD students through the GLaDOS group, focusing on distributed systems verification. He directs the GLaDOS lab at University of Michigan, developing verification frameworks and reliable distributed systems. Current projects include automated proof generation (Basilisk) and efficient communication protocols (Scrooge).
Full Professor at the School of Informatics, Aristotle University of Thessaloniki (AUTh), Greece. Previously served as Associate Professor (2015-2020), Assistant Professor (2008-2015), and Lecturer (2002-2008) at the same institution. Also worked as an Informatics Teacher in Greek Secondary Education from 1989-2002. His research focuses on Learning Technologies with emphasis on Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning, Computational Thinking, Teaching Machine Learning at School, and Massive Open Online Courses (MOOCs). His recent work heavily investigates the application of AI, particularly conversational agents and large language models, in educational contexts. His publications show a strong trend toward AI applications in education, particularly focusing on conversational agents, learning analytics, and automated grading systems. The research spans multiple educational contexts from K-12 to higher education, with particular attention to student self-regulation, collaborative learning, and ethical considerations in AI implementation. 3 Best paper awards at international conferences Interview by Educational Technology Magazine (2013) Cubes Coding project - Winners of Open Education Challenge 2014 Cubes Coding project - Winners of NUMA Competition 2014 Has supervised 5 completed PhD theses, 4 ongoing PhD theses, over 60 Master's theses, and over 120 undergraduate theses. Led the colMOOC project (2018-2020), a €999,000 EU-funded project on integrating conversational agents and Learning Analytics in MOOCs. Also coordinated the T4E project (2020-2022) on Teachers' Fast-paced Distance Training on Tele-education and a MOOC in Greek on Introduction to Programming with Python. Previously served as Director of the Software and Interactive Technologies Laboratory (SWITCH Lab) until 2020, Member of AUTH Educational Policy Committee until 2020, and Chair of the Scientific Supervisory Board of the 2nd Experimental Junior High School in Thessaloniki until 2020.
George Vouros is a Professor in the Department of Digital Systems at the University of Piraeus, Greece. He is the head of the AI Lab (http://ai-group.ds.unipi.gr/ai-group/) and director of the MSc in Artificial Intelligence program in collaboration with the Institute of Informatics and Telecommunications at NCSR Demokritos. He completed his BSc in Mathematics (1986) and PhD in Artificial Intelligence (1992) at the University of Athens. His research focuses on Expert Systems, Knowledge Management, Multi-Agent Systems, Reinforcement Learning, and Mobility Analytics. He has served as program chair and committee member for major conferences (AAMAS, AAAI, IJCAI) and editorial roles in journals like Discover Artificial Intelligence (Springer Nature) and Information (MDPI). He has supervised 13 PhD students and currently oversees 4. His work spans EU-funded projects and national initiatives, emphasizing scalable mobility analytics, air traffic management automation, and ontology engineering. He is also President of the Hellenic A.I. Society and actively promotes interdisciplinary applications of AI in healthcare, transportation, and environmental monitoring. Recent research highlights include deep reinforcement learning for tactical air traffic conflict resolution, LLM-integrated ontology engineering, and multimodal generative adversarial imitation learning for flight trajectory modeling. His work bridges theoretical advancements with real-world applications in critical infrastructure systems.
Maria Virvou serves as Professor and Chair of the Department of Informatics at the University of Piraeus, where she also directs the Graduate Program in Informatics and leads the Research Laboratory 'Software Technology'. She holds significant institutional leadership roles including membership in the University Senate and has chaired the Department of Informatics for multiple terms. As Editor-in-Chief of Springer book series 'Learning and Analytics in Intelligent Systems' and 'Artificial Intelligence-Enhanced Software and Systems Engineering', she maintains substantial academic influence across international scholarly platforms. Dr. Virvou earned her PhD in Computer Science and Artificial Intelligence from the University of Sussex with a scholarship from the State Scholarships Foundation, a Master of Science in Computer Science from University College London, and her undergraduate degree from the Department of Mathematics at the National and Kapodistrian University of Athens. Her educational background in both mathematics and computer science has provided a strong foundation for her interdisciplinary research approach. Professor Virvou's research spans Software Technology, Artificial Intelligence, Educational Software and Games, User Modeling, and Human-Computer Interaction. She has pioneered work in personalized interactive software systems, applying fuzzy logic and machine learning techniques to create adaptive educational environments. Her recent work demonstrates a strategic expansion into AI applications for healthcare, with significant contributions to medical diagnostics using large language models and multimodal AI systems. She has also made notable advances in smart tourism applications through personalization techniques. With over 400 publications to her name, Professor Virvou's scholarly output shows a clear progression from foundational work in user modeling toward increasingly sophisticated AI applications across multiple domains. Her publication trends reveal a strategic focus on explainable AI, multimodal systems, and practical implementations that bridge theoretical advances with real-world applications, particularly in healthcare and education sectors. Ranked #1 worldwide in 'User Modelling' publications (147,450 total publications) according to Scopus Ranked #1 worldwide in 'Educational Software' publications according to both Scopus and Microsoft Academic Search Recognized among the top 2% of most influential Artificial Intelligence scientists worldwide by Stanford University General Co-Chair at the 14th IISA Conference 2023 Invited Keynote Speaker at the 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023) As Director of the Research Laboratory 'Software Technology', Professor Virvou has built a robust research team focused on AI applications across multiple domains. She co-founded and co-chairs the IEEE Intelligent Information Systems and Applications international conference series, creating a significant platform for scholarly exchange. Her leadership extends to editorial roles with major academic publishers and active participation in international research collaborations that have secured substantial funding for innovative projects in AI and software engineering.
Jovan Stojkovic is an incoming Assistant Professor at the Department of Computer Science at the University of Texas at Austin, set to join in Fall 2026. Prior to his appointment at UT Austin, he will spend a year at Meta working with the AI and Systems Co-design group. His research focuses on cloud computing and datacenters, with particular emphasis on cloud-native workloads and machine learning inference. Education: PhD in Computer Science from the University of Illinois at Urbana-Champaign, advised by Professor Josep Torrellas Undergraduate studies at the School of Electrical Engineering, University of Belgrade, Serbia, where he was recognized as the best student of the Computer Engineering and Information Theory Department every year from 2017-2020 Research Interests: Jovan's research focuses on cloud computing and datacenters , with two primary domains: Cloud-native workloads , such as microservices and serverless computing. He investigates how to co-design novel hardware platforms and software systems that deliver orders-of-magnitude improvements in performance, energy efficiency, and resource utilization for these emerging workloads. Machine Learning (ML) inference , particularly large language models (LLMs). His work addresses the challenges of ML inference through smart scheduling, workload placement, and system-level configuration tuning to reduce energy, power, and thermal overheads while maintaining performance and accuracy guarantees. Publication Trends: Jovan's publications demonstrate a strong focus on optimizing cloud infrastructure for emerging workloads. His research spans across serverless computing, microservices, and large language model inference. A clear trend emerges in his work: addressing the performance, energy efficiency, and resource utilization challenges of modern cloud workloads through innovative hardware-software co-design approaches. His most recent work shows increasing focus on LLM inference optimization, particularly in the areas of thermal management, power efficiency, and scheduling for many-adapter environments. Awards and Honors: HPCA Best Paper Award (2025) IEEE MICRO Top Picks Honorable Mention (2024) 6 patents with IBM and Microsoft on: Serverless systems, Processor overclocking in the cloud, and Energy-efficient LLM inference W. J. Poppelbaum Memorial Award (2025) for hardware and architecture innovation Mavis Future Faculty Fellowship (2024–2025) Invited to present at 11th Heidelberg Laureate Forum (2024) Kenichi Miura Award (2022) for excellence in High Performance Computing Multiple student travel grants to ISCA, MICRO, ASPLOS, and HPCA Advising and Grants: Jovan is actively seeking prospective PhD students for his research group at UT Austin. His research has been supported through collaborations with major tech companies including IBM, Microsoft, and Meta. His six patents with IBM and Microsoft demonstrate the practical impact of his research in serverless systems, processor overclocking, and energy-efficient LLM inference. His work on serverless computing (MXFaaS, EcoFaaS) and LLM inference optimization has received significant recognition in top-tier computer architecture conferences. Research Groups: During his PhD at UIUC, Jovan worked with Professor Josep Torrellas on cloud infrastructure research. He has collaborated extensively with researchers at IBM Research (particularly Hubertus Franke) and Microsoft (particularly Íñigo Goiri and Ricardo Bianchini). His upcoming position at UT Austin will establish his independent research group focused on cloud computing and datacenter systems. His year at Meta working with the AI and Systems Co-design group will further strengthen his expertise in AI infrastructure.
Manolis Koubarakis is a Professor and Director of Graduate Studies at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. He is affiliated with the Archimedes Unit at Athena Research Center and is a member of ELLIS. His research focuses on Artificial Intelligence and Data Science, particularly in Linked Geospatial Data, Earth Observation, and Knowledge Graphs. Education: PhD in Computer Science (National Technical University of Athens), M.Sc. in Computer Science (University of Toronto), and B.Sc. in Mathematics (University of Crete). Research Interests: His work spans AI applications in geospatial data, entity resolution, ontology-based data access (OBDA), and semantic web technologies. He leads projects like ExtremeEarth (AI for Copernicus data) and LEO (linked Earth Observation data). Awards: 2015: Fellow of the European Association of Artificial Intelligence (EurAI) 2022: Best Demo Award at CIKM for Copernicus App Lab Advising & Grants: Supervises students in AI and data science. Collaborates on EU-funded projects like BigDataEurope and participates in initiatives like the Standing Scientific Committee for AI in Greece's justice system. Labs & Teams: Heads the AI Lab (ai.di.uoa.gr) and contributes to the MaDgIK group, focusing on data and knowledge management systems.
Ioannis Tzimas is a Professor at the Department of Electrical and Computer Engineering of the University of Peloponnese. He is a highly active researcher with numerous publications in areas of Service-Oriented Architectures, Web Engineering, Big Data, and Artificial Intelligence applications. University: University of Peloponnese Department: Department of Electrical and Computer Engineering Academic Rank: Professor Email: tzimas@uop.gr Ioannis Tzimas received his education from the Department of Computer Engineering and Informatics of the University of Patras, where he also completed his PhD in Web Engineering. His research spans multiple interdisciplinary domains at the intersection of computer science and practical applications. Service-Oriented Architectures and Information Systems Web Data Engineering and Web Modeling Big Data Management and Data Science Machine Learning and Artificial Intelligence Applications Digital Ecosystems and Digital Transformation for the Public Sector Bioinformatics Professor Tzimas' recent research output demonstrates a strategic focus on applying advanced computational techniques to address contemporary challenges. His work shows particular expertise in labor market analysis using large language models, electricity demand forecasting in Greece, and social protection systems. His publications reveal a pattern of bridging theoretical computer science with practical, real-world applications across multiple sectors. Since 2018, he has served as an international consultant to the World Bank in the field of information systems and digital transformation, working on projects across Europe, Africa, the Caribbean, the Pacific Islands, and China. His earlier career included significant technical leadership roles at the University of Patras and other Greek institutions. Technical Manager of the Graphics, Multimedia and Geographic Systems Laboratory (1996-2018) Technical Coordinator of the Internet and Multimedia Technologies Research Unit (1997-2011) Scientific Manager of the Network Management Center of the TEI of Messolonghi (2009-mid 2013)
Alvin Cheung is an Associate Professor in the Computer Science Division at UC Berkeley's EECS department. He is affiliated with the Data Systems and Foundations group, Programming Systems group, Sky Lab, and SLICE Lab, and serves as a faculty affiliate at the Berkeley Institute for Data Science. He advises the Data Science Discovery Program and provides technical guidance to industry partners. His research spans data management, programming languages, and scalable software systems, with emphasis on helping users process large datasets efficiently. Key innovations include verified lifting (applying formal methods and ML to infer program properties) and systems for optimizing database-backed applications and geospatial analytics. Recent work explores LLM-driven code optimization and transpilation techniques. His publications (2023-2025) show strong trends in ML-enhanced systems, verified compilation, and data management tools. Articles frequently integrate formal methods, program synthesis, and hardware-aware optimizations across domains like databases, distributed computing, and HCI. Scientific Awards: ACSIC Rock Star Award (2025) Dahl-Nygaard Junior Prize (2024) VLDB Early Career Research Contribution Award (2023) IEEE TCDE Rising Star Award (2020) Sloan Fellowship (2019) NSF CAREER Award (2017) 20+ additional honors Advising & Grants: He mentors PhD/MS students (e.g., Lily Liu at OpenAI, Chenglong Wang at Microsoft Research). Research is funded by: NSF DOE ONR ARO Intel Notable grants include ONR Young Investigator Award and ARO Early Career Program Award. Labs & Teams: Leads projects in Berkeley's Data Systems/Programming Systems groups and collaborates with Sky Lab/SLICE Lab. Manages labs focused on verified compilation (e.g., Tenspiler) and data infrastructure (e.g., Spatialyze).
Michalis Mountantonakis is a Postdoctoral Researcher at FORTH and Laboratory Teaching Staff in the Department of Computer Science at the University of Crete, Greece. He holds a PhD (2020), MSc (2016), and BSc (2014) in Computer Science from the University of Crete, all with top grades. His research focuses on Large-Scale Semantic Data Integration, Linked Open Data, and Semantic Web technologies, with over 45 publications in top venues like ACM VLDB, ISWC, and ECML. He has been awarded the prestigious SWSA Distinguished Dissertation Award (2020) and the Maria Michael Manasaki Fellowship (2020). His work includes tools like LODsyndesis and LODChain, addressing challenges in knowledge graph connectivity and validation of AI-generated content. Education: PhD in Computer Science (2016-2020), University of Crete (Excellent GPA 9.74/10) MSc in Computer Science (2014-2016), University of Crete (Excellent GPA 9.87/10) BSc in Computer Science (2010-2014), University of Crete (2nd in class with GPA 8.42/10) Research Interests: His work bridges semantic web technologies with modern AI challenges, emphasizing large-scale data integration, knowledge graph applications, and validation frameworks. He has contributed to cultural heritage informatics, machine learning-augmented semantic systems, and cross-lingual NLP solutions. Recent trends include leveraging LLMs for query generation and semantic enrichment while ensuring factual accuracy through knowledge graph-driven validation. Key Achievements: Developed LODsyndesis, a global-scale semantic integration service Pioneered real-time validation of ChatGPT responses using RDF knowledge graphs Won Best Paper Award (ISWC 2022) for entity enrichment techniques Recipient of Stelios Orphanoudakis Undergraduate Fellowship (2013-2014) Participated in Roche Continents 2019 (top 100 European science students) Grants & Labs: His research has been supported by GSRT/HFRI. He collaborates with FORTH-ICS and leads projects in EU-funded initiatives like iMarine and BlueBridge. Current work focuses on governance models for ontologies, interoperable thesaurus creation (e.g., FoodEx2), and semantic analytics for cultural heritage datasets.
Professor Manolis Koubarakis is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on geospatial data science, knowledge graphs, entity resolution, and AI applications in Earth observation. He leads projects like ExtremeEarth and Plato, advancing semantic data cube systems and geospatial question answering engines. His work bridges AI and geospatial technologies, with contributions to frameworks like pyJedAI and Strabo 2 for managing big geospatial data. Research Interests include: Geospatial Question Answering Systems Entity Resolution and Entity Linking Ontology-Based Data Access (OBDA) Knowledge Graph Construction and Applications Earth Observation Data Analytics AI for Geoinformatics Notable Projects: ExtremeEarth: Combines Copernicus satellite data with machine learning for environmental analytics. Plato: Semantic data cube system enabling advanced querying of multidimensional datasets. GeoQA2: A geospatial question answering engine evaluated on large benchmarks. JedAI Family: Tools for scalable entity resolution in structured/semi-structured data. His publications span 20+ years, with recent emphasis on: AI-driven Earth observation systems Geospatial RDF benchmarking 3D geospatial interlinking Large language models for legal and health content delivery
Christos Ouzounis is a Professor of Bioinformatics at the Department of Informatics, Aristotle University of Thessaloniki , with a career spanning institutions including the European Bioinformatics Institute , King's College London , and University of Toronto . His work bridges Computational Biology , Digital Biology , and Metagenomics , focusing on large-scale data analysis, machine learning applications, and functional annotation of proteins. Education : BSc in Biological Sciences (1986), MSc in Biological Computation (1987), and DPhil in Computational Chemistry (1993) Key Roles : Director of the Bioinformatics Centre at King's College London (2007-2010), Research Director at IDEP-EKETA (2014-2020) His research interests include low-complexity protein sequences , Covid-19 seasonality patterns linked to UV radiation, and metagenomic analysis of urban microbiomes in cultural heritage sites. Current projects involve machine learning models for microbial coexistence networks, ontological classification of biomedical literature, and bioinformatics tool development . Publications highlight trends in archaeal genomics , functional dark matter in metagenomics, and epidemiological modelling . Notable collaborations include work on BioTextQuest v2.0 for concept discovery and MjCyc for metabolic pathway analysis.
Nick Bassiliades is a Professor at the School of Informatics , Aristotle University of Thessaloniki , Greece. His academic roles include serving as President of the Digital Governance Committee and the Digital Transformation of Greek Universities Committee, as well as Director of the Web, Data, and Knowledge Engineering Sector. Education: B.Sc. in Physics, Aristotle University of Thessaloniki (1991) M.Sc. in Applied Artificial Intelligence, University of Aberdeen (1992) Ph.D. in Parallel Knowledge Base Systems, Aristotle University of Thessaloniki (1998) His research focuses on Semantic Web , Ontologies , Knowledge Graphs , and applications in Artificial Intelligence , eGovernment , and Intelligent Agents . Recent publications emphasize ontological frameworks for requirements engineering, explainable AI, and electric vehicle knowledge graphs. He actively contributes to scientific communities as a Senior Member of IEEE and ACM , and serves as Co-Editor-in-Chief for the International Journal of Artificial Intelligence in Business and Management . His work involves collaborations with the Intelligent Systems laboratory and projects like XR4DRAMA for disaster management.
