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).
Elias Flytzanis serves as a Professor in the Department of Informatics at the School of Information Sciences and Technology, Athens University of Economics and Business (AUEB). With a strong academic foundation in physics and advanced degrees from prestigious institutions, he contributes to the academic and research mission of one of Greece's leading informatics departments. Dr. Flytzanis holds a Bachelor's degree in Physics from Harvard University, complemented by a Master of Arts and Ph.D. from the University of Wisconsin. His educational background bridges theoretical physics with computational approaches, positioning him at the intersection of scientific computing and information technology. His research interests span computational physics, scientific computing, and data analysis methodologies. These fields leverage his physics background while addressing contemporary challenges in computer science and information systems. The Department of Informatics at AUEB focuses on cutting-edge research in computer science, information systems, and data science, providing an appropriate academic home for his interdisciplinary expertise. As a faculty member at AUEB, Professor Flytzanis contributes to both undergraduate and postgraduate education programs, including the Department's offerings in Computer Science, Information Systems, Data Science, and Mathematics of Market and Production. The department maintains active research laboratories and participates in numerous national and international research projects.
Amalia Foka is an Assistant Professor in Computer Science Applications for the Arts at the Department of Fine Arts & Art Sciences , School of Fine Arts , University of Ioannina , Greece. She has held academic positions at the University of Patras (2005-2013), University of Ioannina (2005-2008), and Computer Technology Institute & Press "Diophantus" (2014-2015). Her research bridges Artificial Intelligence with Digital Art , focusing on Generative AI , Social Media Mining , and Human-Computer Interaction within artistic contexts. Education: BEng in Computer Systems Engineering (1998) from the University of Manchester Institute of Science & Technology (UMIST) , UK MSc in Advanced Control (1999) from UMIST PhD in Robotics (2005) from the Department of Computer Science , University of Crete Her artistic research includes projects like Bushwalking (StyleGAN2 landscape generation), Breaking the Silence (NLP analysis of taboo topics), and The Invisible Structures of the Artworld (social media-driven network visualization). She leads the Multimedia Lab at the University of Ioannina, focusing on AI in Creative Processes and Digital Interaction methodologies.
Prof. Dimitris Gizopoulos is a Professor at the Department of Informatics & Telecommunications, University of Athens, leading the Computer Architecture Laboratory. His research focuses on fault tolerance, design validation, performance, and energy efficiency in microprocessors, GPUs, and AI accelerators. He is an IEEE Fellow (2013) and ACM Distinguished Member (2022). His work is supported by Horizon Europe projects like DARE, Neuropuls, and Vitamin-V, alongside industry grants from AMD, Cisco, and Meta. He participates in networks like HiPEAC and Eurolab4HPC and serves on editorial boards of journals including ACM Computing Surveys and IEEE Transactions on Computers . Prof. Gizopoulos teaches Computer Architecture courses at both undergraduate and graduate levels. His research spans cross-layer reliability analysis, voltage scaling effects, and secure hardware design. Notable contributions include frameworks for GPU reliability assessment (GUFI, GPUI-4) and tools like MerLIN for microarchitecture-level analysis. His lab’s work has been funded by the EuroHPC Joint Undertaking and the Greek-China Research Collaboration program. Key Projects: DARE (RISC-V Europe), Neuropuls (neuromorphic accelerators), Vitamin-V (RISC-V cloud environments). Awards: IEEE Fellow (2013), ACM Distinguished Member (2022), IEEE Golden Core (since 2002). Industry Partnerships: AMD, Cisco, Bosch, NVIDIA, Intel, IBM Research. Labs: Leads the Computer Architecture Lab, focusing on fault tolerance and energy-efficient computing. His work emphasizes bridging hardware-software co-design challenges, with publications in top venues like IEEE Transactions on Computers and ACM Computing Surveys . Recent efforts include analyzing silent data corruptions (SDCs) in CPUs and GPUs, and developing validation frameworks for cloud-native architectures.
Mohsen Lesani is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin School of Engineering. His research focuses on reliability and security of software systems, particularly concurrent and distributed systems, with recent emphasis on secure replicated systems and distributed machine learning. Dr. Lesani received his PhD from UCLA, MS in artificial intelligence from Sharif University of Technology, and BS in software engineering from University of Tehran. He was previously a postdoc at MIT. His educational background provides a strong foundation for his interdisciplinary research spanning programming languages, distributed systems, and security. His research interests center on creating reliable and secure distributed systems. Current projects include resilient and secure distributed systems, heterogeneous and reconfigurable secure distributed systems, automatic analysis and synthesis of replicated objects, verification of distributed systems, data analytics, secure exchange across blockchains, machine learning for performance models, domain-specific languages and type systems, and automatic fence insertion for concurrent systems. His work bridges theoretical foundations with practical implementations to address real-world challenges in distributed computing. Lesani's research has been recognized with several prestigious awards including the NSF CAREER award in 2020 and DARPA YFA award in 2022. His work has also received the SIGPLAN Research Highlight in 2019, a distinguished paper award at OOPSLA 2018, and a best paper award at ISSRE 2015. These accolades reflect the impact and quality of his contributions to the field. He actively mentors PhD students in the Safe and Secure Software (S3) lab, including Xiao Li, Eric Chan, Javad Saber-Latibari, and Tejas Mane. His research has been supported by multiple NSF grants, demonstrating sustained funding for his innovative work. Lesani serves on program committees for major conferences including POPL, PLDI, OOPSLA, and DISC, contributing to the academic community. Lesani leads the Safe and Secure Software (S3) lab at UC Santa Cruz, where his team works on cutting-edge research in distributed systems, programming languages, and security. The lab fosters a collaborative environment where theoretical insights are translated into practical systems that address real-world challenges in reliability and security of distributed applications.
Prof. Nikos Mamoulis is a Professor at the Department of Computer Science & Engineering, University of Ioannina, and a Lead Researcher at Archimedes Research Unit, ATHENA RC. He holds a PhD from Hong Kong University of Science and Technology (HKUST) and a Diploma from the University of Patras. His research focuses on spatial data management, big data analytics, data privacy, and uncertain data systems. Education : Ph.D., Computer Science, Hong Kong University of Science and Technology (2000) 5-year Diploma, Computer Engineering and Informatics, University of Patras (1995) Research Interests : Complex data management (spatial, spatio-temporal, time-series, text, graphs), big data analysis, privacy preservation, and uncertain data systems. He develops scalable algorithms and systems for modern data management challenges, with applications in transportation, social networks, and geospatial analytics. Projects & Grants : MESA: In-memory Spatial Analytics Made Scalable (HFRI-funded, PI) MORE: Real-time Energy Data Management (H2020, Senior Researcher) Smart City Bus Platform (ERDF-funded, PI/Coordinator) Awards : Outstanding Young Researcher Award (2008-2009, HKU) Best Paper Award at SSTD 2015 Test of Time Award at MDM 2022 Labs & Collaborations : Leads the Archimedes Research Unit at ATHENA RC, collaborating with institutions like HKUST and Uppsala University on spatial and big data systems. Active in organizing top-tier conferences like SIGMOD, EDBT, and ICDE.
Ioannis Panageas is an Assistant Professor in Computer Science at UC Irvine's Donald Bren School, directing the GOALLab. His research develops theory for learning in multi-agent systems, game dynamics, and optimization. Funded by NSF and NRF, he focuses on last-iterate convergence guarantees in games, efficient equilibrium computation, and multi-agent reinforcement learning. Recent Work: Provides first exponential lower bounds for fictitious play in potential games (NeurIPS 2023), efficient Nash equilibrium computation methods (ICLR 2023), and semi-bandit learning dynamics with no-regret guarantees (ICML 2023). Teaching: Offers courses in Algorithmic Game Theory and Optimization for Machine Learning. Currently advising 3 PhD students and 2 MS students.
Athanasios Rontogiannis is an Associate Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA). He holds a PhD in Signal Processing from the National University of Athens (1997) and has held roles including Research Director at the National Observatory of Athens (2017–2021). His research focuses on signal processing, machine learning, and hyperspectral image analysis. Education: MEng (Electrical Engineering, NTUA, 1991), M.A.Sc. (University of Victoria, Canada, 1993), PhD (Signal Processing, National University of Athens, 1997). Research interests include adaptive algorithms, sparse representations, and tensor models. He has served on editorial boards of IEEE Transactions on Signal Processing and EURASIP journals, receiving an honorary distinction in 2020. He is a Senior Member of IEEE and affiliated with EURASIP and the Technical Chamber of Greece. Key contributions span hyperspectral unmixing, Bayesian algorithms, and space data exploitation. His work integrates machine learning for applications in space science and signal processing.
Ioannis Z. Emiris is a Professor in the Department of Informatics & Telecoms at the National & Kapodistrian University of Athens and concurrently serves as President and General Director of the ATHENA Research Center in Greece. He holds a BSc in Computer Science from Princeton University (1989) and a PhD in Computer Science from UC Berkeley (1994). His research spans computational geometry, algebraic algorithms, robotics, structural bioinformatics, and optimization. He is a leading expert in sparse elimination theory, geometric modeling, and algorithmic algebra. Affiliations: ATHENA Research Center, National & Kapodistrian University of Athens, INRIA Sophia Antipolis (France via joint AROMATH team). Education: BSc (Princeton), PhD (UC Berkeley). Research Interests Emiris's work focuses on geometric algorithms, algebraic systems, and their applications. His contributions include advancements in sparse elimination theory, computational geometry for high-dimensional data, and robotics. He has developed algorithms for polynomial system solving, Voronoi diagrams, and geometric predicates for ellipses. Articles Overview His recent work bridges theoretical advances with practical applications, such as deep learning for protein structure prediction (HydraProt) and geometric algorithms for high-dimensional data analysis. He explores intersections between algebraic geometry and computational methods, with applications ranging from robotics to bioinformatics. Scientific Awards Best Paper Award at ISSAC 2003 and 2010 MSCA Network GRAPES (2019-2023) Advising & Grants Emiris has supervised numerous students and researchers, contributing to interdisciplinary projects. He has secured grants for initiatives like the GRAPES network and has led teams in algorithm design and geometric software development. His work on MARS (Maple/Matlab/C Resultant-Based Solver) exemplifies his focus on practical algorithm implementation. Labs & Teams He directs the Lab of Geometric & Algebraic Algorithms and collaborates with the AROMATH team at INRIA. His research group develops open-source tools for computational geometry and algebraic computations.
Dr. Jean-Christophe Nave is an Associate Professor in the Department of Mathematics and Statistics at McGill University. He holds a PhD from the University of California, Santa Barbara (2004), under advisors Xu-Dong Liu and Sanjoy Banerjee. Prior to McGill, he served as a Lecturer and Instructor at MIT's Mathematics Department (2005-2010). His research focuses on numerical analysis, partial differential equations, fluid mechanics, and computational methods for interface problems. He has led research groups involving postdocs, PhD, and undergraduate students, collaborating on projects like the Correction Function Method for PDEs and the Characteristic Mapping Method for advection problems. Education: Ph.D. in Applied Mathematics from UCSB (2004). Affiliations include the Institut des Sciences Mathematiques Steering Committee, Centre de Recherches Mathematiques Applied Math Lab, and CNRS-UMI. Active in teaching courses like Numerical Analysis I/II and Non-Linear Dynamics at McGill, with sabbatical periods noted in recent years. Research interests span numerical methods for PDEs, fluid-structure interaction, and multi-phase flows. His work integrates computational geometry and invariant numerical techniques, addressing challenges in complex fluid dynamics and interface-driven phenomena. Over 40 peer-reviewed publications and continuous contributions to the field of computational applied mathematics. Scientific advising includes over 20 graduate and undergraduate students, with notable alumni now in academia and industry. Collaborations include projects on volcano dynamics, fiber drawing instabilities, and concentrated solar power systems. His methods have advanced numerical simulations for engineering and physical systems involving discontinuous coefficients and sharp interfaces.
Timothy M. Jones is a Professor of Computer Architecture and Compilation at the University of Cambridge Computer Laboratory, where he leads research in systems-level computing. He is also a Fellow at Gonville and Caius College, contributing to academic leadership and student mentorship within the collegiate system. His primary affiliation with the Computer Laboratory positions him at the forefront of systems research within the university. Dr. Jones's research focuses on extracting various forms of parallelism (thread-level, data-level, memory-level) to enhance computational performance while addressing energy efficiency and reliability challenges. His work spans compiler design, binary translation, and microarchitecture optimization, with specific interest areas including: Compiler technologies for functional and parallel programming Hardware reliability and fault tolerance mechanisms Binary analysis and instrumentation frameworks Memory system optimization and virtual memory management Security enhancements through binary modification Runtime systems for heterogeneous architectures Analysis of his recent publications reveals strong emphasis on systems-level innovation, particularly in fault tolerance techniques, binary analysis tools, memory optimization, and parallel execution frameworks. His work consistently bridges theoretical computer science with practical hardware implementation challenges. Dr. Jones maintains active participation in the academic community through conference leadership roles, including serving as Program Co-Chair for CGO 2026 and committee positions at premier venues including ISMM, CGO, and ECOOP. He contributes to open-source academic resources through GitHub and maintains professional engagement via Twitter.
Theodora Varvarigou is a Professor in the Department of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). She holds a B.Eng. from NTUA and M.Eng. and Ph.D. degrees from Stanford University. Her career includes research at AT&T Bell Labs and roles at the Technical University of Crete. From 2008-2012, she served as director of NTUA's 'Technoeconomic Systems' postgraduate program. Her research focuses on Cloud Computing, Multimedia Content Processing, Social Networking Technologies, and emerging areas like blockchain, edge computing, and cybersecurity. She has published over 200 papers and led numerous European research projects, emphasizing scalable systems, data management, and smart infrastructure applications. Her work spans technical innovations such as intrusion detection systems, edge resource optimization, and blockchain-based solutions for IoT, healthcare, and smart cities. Recent publications highlight advancements in AI-driven resource allocation, privacy-preserving blockchain designs, and predictive analytics for edge computing environments. Professor Varvarigou has contributed to interdisciplinary initiatives, including cohort data harmonization in biomedical research and social media analytics for urban planning. Her teaching includes courses on digital systems, network programming, and fault-tolerant systems.
Matthias Bucher is a Professor at the Department of Electronics and Computer Engineering, Technical University of Crete. He specializes in analog/RF integrated circuits design, MOSFET compact modeling, and device characterization. His research focuses on nanoscale CMOS, wide-band semiconductor devices, and high-voltage MOSFETs. He leads the Electronics Laboratory and teaches courses such as Electronics II and CMOS Analog IC Design. Education: Ph.D. in Electrical Engineering, Swiss Federal Institute of Technology (EPFL), 1999 M.S. in Electrical Engineering, Swiss Federal Institute of Technology, 1993 Research Interests: Prof. Bucher’s work emphasizes charge-based compact models (e.g., EKV3), RF device modeling, and noise analysis in MOSFETs/JFETs. His contributions include open-source tools for Verilog-A modeling and parameter extraction methodologies for advanced CMOS technologies. Labs/Teams: He directs the Electronics Laboratory , focusing on nanoelectronics and high-reliability circuits. His team collaborates on semiconductor device modeling for aerospace and industrial applications. Grants/Awards: While not explicitly listed, his extensive publication record and leadership in open-source projects indicate sustained recognition in semiconductor research communities.
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.
Dimitris Mitropoulos is an Assistant Professor at the National and Kapodistrian University of Athens (NKUA) in the Department of Business Administration, where he teaches courses on Distributed Ledger Technologies, Data Security and Privacy, Algorithms and Business Analytics, and Introduction to Programming. He also serves as Head of the Reliability Engineering Directorate at the National Infrastructures for Research and Technology (GRNET), Greece's national research and education network organization. Previously, he was a Postdoctoral Researcher in the Computer Science Department at Columbia University. Dr. Mitropoulos received his Ph.D. degree in Secure Software Development Technologies from the Athens University of Economics and Business (AUEB) in 2014. His doctoral research was supported by the Heracleitus II Scholarship, co-financed by the European Union and Greek national funds. He is a member of prestigious professional organizations including ACM, IEEE, and USENIX. Dr. Mitropoulos conducts pioneering research at the intersection of software engineering and cybersecurity, with particular expertise in secure software development, vulnerability analysis, and blockchain security. His work spans multiple dimensions of software security including code injection attacks, infrastructure as code security, smart contract analysis, and dependency management in software ecosystems. His research methodology combines static and dynamic analysis techniques with empirical studies of real-world software systems, particularly focusing on Java, Python, and Solidity ecosystems. His recent work has made significant contributions to understanding security vulnerabilities in modern software development practices and infrastructure management. Dr. Mitropoulos has received numerous prestigious awards for his research contributions, including the Research Excellence Award from NKUA (2025), Distinguished Paper and Artifact Awards at PLDI '22, Best Data Showcase Award at MSR 2018, and multiple postdoctoral research funding scholarships. His work on "Finding typing compiler bugs" was recognized with both Distinguished Paper and Artifact Awards at PLDI '22, highlighting the significance and reproducibility of his research. He has also received recognition for his service to the academic community, including a Certificate of Appreciation from ESEC/FSE '21 for his contributions to conference organization. Dr. Mitropoulos has been actively involved in securing research funding and leading significant research projects. He currently serves as Principal Investigator for the SecOPERA project (2023-Today), funded by the European Commission under Horizon Europe. Previously, he contributed to several major EU and US-funded projects including eSSIF-Lab (2019-2022), FASTEN (2019-2022), PRIViLEDGE (2018-2021), CERTCOOP (2017-2020), PANORAMIX (2016-2019), and TREDISEC (2016-2018). His research has been supported by diverse funding sources including the European Commission's Horizon 2020 program, the National Science Foundation, and the Defense Advanced Research Projects Agency (DARPA). Dr. Mitropoulos plays an active role in the international research community through various leadership positions. He serves on program committees for top-tier conferences including OOPSLA (2026), ICSE (2026), ESEC/FSE (2025), and ISSTA (2025). He has previously served as Workshop Co-Chair for ISSTA 2025 and Student Volunteer Chair for ESEC/FSE 2021. His contributions to mentoring the next generation of researchers include serving as a mentor for the ICSE Student Mentoring Workshop (2022) and supervising Google Summer of Code projects (2017).
