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 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.
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 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.
Dimitrios Zoros holds the position of Lecturer at the Department of Mathematics of the National and Kapodistrian University of Athens (NKUA). His primary affiliations include NKUA and the MPLA (MPLA's formal English name?). He is actively involved in teaching courses such as Recursion Theory and Data Structures. His research focuses on Graph Theory, Parameterized Complexity, and related areas. Education: BSc in Mathematics from NKUA, MSc in Logic, Algorithms, and Computation from MPLA, and a PhD in Logic and Algorithms from NKUA under Prof. Dimitrios M. Thilikos. Research Interests: Graph Obstruction Sets, Graph Searching, Parameterized Complexity, Computability, Algorithms, Logic/Set Theory, and Discrete Mathematics. His work contributes to theoretical foundations of algorithms and graph theory applications.
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.
Christos Kaklamanis is a Full Professor and Chair of the Department of Computer Engineering and Informatics at the University of Patras, Greece, with significant leadership roles including President of Computer Technology Institute & Press "Diophantus" (CTI) from 2016-2021. His academic career includes serving as Vice-Chair of the Department (2009-2011 and 2003-2005) and Director of the Division of Applications and Foundations of Computer Science (1997-2003). Dr. Kaklamanis earned his S.B. in Computer Science and Engineering from MIT (1986), followed by S.M. (1989) and Ph.D. (1992) from Harvard University. He completed postdoctoral work at DIMACS (Center for Discrete Mathematics and Theoretical Computer Science) and worked as a research consultant for NEC Research Institute, Princeton. His research spans theoretical and applied computer science with expertise in algorithm design, computational complexity, communication networks, parallel and distributed computing, and algorithmic game theory. He has made significant contributions to network algorithms, particularly in optical networks and wireless communication, with recent expansion into computational social choice and educational technology applications. His work bridges theoretical foundations with practical implementations, especially in developing educational tools that make complex algorithms accessible. Analysis of his publication history reveals an evolution from foundational algorithm research toward practical applications of theoretical concepts, particularly in educational technology and community-oriented computing solutions. His recent work focuses on creating web and mobile applications that address real-world challenges in campus management, cultural tourism, and community engagement while maintaining strong theoretical underpinnings. Elected member of EATCS council (2009-2021) Active in ACM, IEEE, SIAM, and Technical Chamber of Greece Program Committee Chair for WAOA (Workshop on Approximation and Online Algorithms) Conference co-chair for ICALP (International Colloquium on Automata, Languages and Programming) As an educator, Dr. Kaklamanis has taught core courses including Theory of Computation, Parallel Algorithms, Communication Algorithms, and Cryptography. He has led major research initiatives including EU-FET projects CRESCCO and AEOLUS (as coordinator), EU-ICT Project EULER, and the "DIGITAL SCHOOL" project focused on national educational platforms. His leadership extends to directing research laboratories in Combinatorial Algorithms, Distributed Systems and Telematics, and Pattern Recognition. His current work continues to bridge theoretical computer science with practical applications, particularly in educational technology, with numerous recent publications focused on developing interactive learning tools and platforms that leverage algorithmic principles for educational and community benefit.
Vasileios Metaftsis is a Professor at the Department of Mathematics, University of the Aegean, located in Karlovassi, Samos, Greece. His office is situated in the "Regal Mansion" building (Office B3), and he holds regular office hours Monday through Friday from 10:00 to 12:00. His primary contact email is vmet@aegean.gr. Education: Ph.D. in Mathematics from Heriot-Watt University, Edinburgh, Scotland B.Sc. in Mathematics from the University of Athens, Greece Research Focus: Professor Metaftsis specializes in Geometric Group Theory, with emphasis on hyperbolic and relatively hyperbolic groups, subgroup separability (LERF groups), residual properties (e.g., finiteness, nilpotence), Hopfian groups, linearity of groups, and Lie algebras associated with group structures. His work bridges combinatorial, geometric, and algebraic approaches to group theory. Publication Trends: His 25+ publications (2007–2022) predominantly explore residual properties of groups, automorphisms (especially IA-automorphisms), Lie algebras linked to McCool and Artin groups, HNN-extensions, and topological rigidity. Recent work (2020–2022) focuses on residual nilpotence and the interplay between group theory and Lie algebras. Collaborations include researchers like C. Kofinas and A.I. Papistas. Awards & Honors: No scientific awards or fellowships are documented in available sources. Academic Service: He actively contributes to academia through course instruction (Algebra, Galois Theory) and examination duties at the University of the Aegean. No information is available regarding student supervision, grant funding, or lab affiliations.
Dr. Panagiotis Repoussis serves as Associate Professor of Operations Research and Supply Chain Management at the Department of Marketing and Communication within the School of Business at Athens University of Economics and Business (AUEB). Previously, he held positions as Assistant Professor at Stevens Institute of Technology and visiting Lecturer at the University of Piraeus and Bayes School of Business at City University of London. His academic foundation includes a Diploma in Chemical Engineering from the National Technical University of Athens (2002), followed by graduate studies at Imperial College London and AUEB where he completed his doctoral dissertation in November 2008. His educational trajectory reflects a strategic shift from chemical engineering to operations research specialization. Dr. Repoussis specializes in Operations Research with concentrated expertise in Supply Chain Management , Vehicle Routing and Scheduling , and Production Systems Optimization . His research integrates mathematical modeling with computational intelligence to solve complex combinatorial optimization problems across logistics networks, manufacturing operations, and transportation systems. Key methodological contributions include advanced algorithms for dynamic scheduling under uncertainty and real-time decision support frameworks. Analysis of his 15 most recent publications (2019-2025) reveals a strong research trajectory toward Industry 4.0 applications, with increasing focus on IoT/AGV integration in manufacturing, disruption-resilient logistics, and robust optimization under stochastic conditions. Vehicle routing problems remain his dominant research theme, now extended to cross-docking operations, profit-oriented routing, and humanitarian logistics contexts. As principal investigator, Dr. Repoussis has secured research funding from NSF, EU programs, non-profit organizations, and private sector partners across Europe and North America. His academic service includes editorial board membership for Transportation Research Part E and Advances in Operations Research, leadership roles in the Hellenic Operational Research Society and Production and Operations Management Society, and organization of major conferences including Odysseus and MathSports. His professional activities demonstrate deep engagement with both theoretical advancements and practical implementations, particularly through development of decision support systems for waste management, healthcare logistics, and energy-aware production scheduling. Current initiatives emphasize the convergence of prescriptive analytics with emerging digital technologies in operational planning contexts.
Evi Papaioannou is an Assistant Professor at the Department of Computer Engineering and Informatics , University of Patras. Her research focuses on foundational and applied aspects of algorithms, computational complexity, and distributed systems, with interdisciplinary applications in education and the humanities. Researcher at the Computer Technology Institute & Press (CTI "Diophantus") Teaches courses like Theory of Computation , Parallel Algorithms , and Computational Complexity Research Interests span algorithmic design, wireless networks, game theory, and pedagogical approaches to computational thinking. She also integrates theoretical computer science into educational technology and humanities. Her affiliations include the Division of Applications and Foundations of Computer Science , which oversees research in fundamental principles and emerging areas like high-performance computing, artificial intelligence, and multimedia networks. She contributes to laboratories in combinatorial algorithms, distributed systems, and machine learning.
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.
George Amanatidis is an Assistant Professor in the Department of Informatics at the Athens University of Economics and Business (AUEB) since December 2024 and a Research Associate at the Archimedes Unit of the Athena Research Center since February 2023. His academic career spans multiple international institutions with progressive roles in theoretical computer science and algorithmic economics. His educational qualifications include: PhD in Computer Science (2017) from Athens University of Economics and Business with thesis "Design of algorithms and mechanisms for problems with limited—or no—payoffs" Diploma in Applied Mathematics from National Technical University of Athens Master of Science in Mathematics from Georgia Institute of Technology Dr. Amanatidis specializes in algorithmic problems at the intersection of Discrete Mathematics, Computer Science, and Economics. His research critically examines fair allocation of goods, mechanism design frameworks, and graph sampling methodologies, contributing to foundational advancements in computational social choice and resource distribution theory. His work bridges theoretical computer science with economic modeling to solve complex optimization problems under constraints. No scientific awards are documented in the provided information. While no student advisement details or research grants are specified in the source material, his career trajectory demonstrates sustained engagement with high-impact academic institutions including the University of Essex, University of Amsterdam, Sapienza University of Rome, and CWI Netherlands. His current research activities at the Archimedes Unit focus on algorithmic design and computational theory, leveraging interdisciplinary approaches to address challenges in economic modeling and discrete systems.
Işıl Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her academic career spans over a decade of significant contributions to programming languages research, particularly in program analysis, verification, and synthesis. Dr. Dillig received all her academic degrees (BS, MS, and PhD) from Stanford University before joining the faculty at UT Austin. Her educational background established the foundation for her innovative research approach that bridges theoretical computer science with practical applications. Her research focuses on developing techniques to make software systems more reliable, secure, and easier to build through advanced program analysis, verification, and synthesis methods. She has pioneered approaches that combine symbolic reasoning with machine learning to tackle complex software engineering challenges across multiple domains including security, databases, and programming language theory. Her work demonstrates exceptional depth in creating practical tools that address real-world software development problems while maintaining strong theoretical foundations. Analysis of Dr. Dillig's publication record reveals a consistent trajectory of innovation in program synthesis, with recent work expanding into neurosymbolic approaches that bridge neural networks with formal methods. Her research shows strong connections between theoretical foundations and practical applications, particularly in security-critical systems, database technologies, and blockchain applications. The evolution of her work demonstrates increasing sophistication in handling complex program structures while maintaining practical usability. Dr. Dillig has received prestigious recognition for her research contributions: Sloan Fellowship NSF CAREER award As a dedicated educator and research leader, Dr. Dillig has served in significant roles including Program Chair for PLDI 2022 and Steering Committee member for PLDI. She has mentored numerous students through her UToPiA research group, guiding research in program synthesis, verification, and analysis. Her work has been supported by substantial research grants that have enabled innovative projects at the intersection of programming languages and security. Dr. Dillig leads the UToPiA (UT Austin Programming, Languages, and Analysis) research group, which focuses on developing novel techniques for program analysis, verification, and synthesis. The group maintains strong collaborations with industry partners and academic institutions worldwide, translating theoretical advances into practical tools that address real software engineering challenges.
Yufei Ding is an Associate Professor in the Computer Science & Engineering Department at the University of California, San Diego (UCSD), where she leads the PICASSO Lab. Her research spans domain-specific language design, architecture and compiler optimization, and hardware acceleration, with current focus on developing high-performance, energy-efficient, and high-fidelity programming frameworks for quantum computing and machine learning. Dr. Ding received her Ph.D. in Computer Science from North Carolina State University and a B.S. in Physics from the University of Science and Technology of China. Her interdisciplinary background bridges physics and computer science, enabling her to tackle challenges in emerging computing paradigms. Her research interests focus on Compiler Technology, Machine Learning, and Quantum Computing , with specific expertise in domain-specific language design, architecture and compiler optimization, and hardware acceleration. Dr. Ding's work addresses critical challenges in programming frameworks for emerging technologies, particularly in making quantum computing more accessible and efficient through innovative compiler techniques and runtime systems. Dr. Ding's scientific contributions have been recognized with prestigious awards including the NSF CAREER Award (2020) and the IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High-Performance Computing (2019) . As an active researcher and educator, Dr. Ding serves on program committees for major conferences including PLDI, PPoPP, and SPLASH. She currently has Ph.D. openings in quantum computing and machine learning systems research, as well as a postdoc position in quantum computing for physics Ph.D. candidates with relevant background. Dr. Ding founded and leads the PICASSO Lab at UCSD, which focuses on developing innovative solutions for programming emerging computing technologies. The lab's work bridges theoretical foundations with practical implementations to address real-world challenges in high-performance computing.
Shachar Itzhaky is an Associate Professor in the Department of Computer Science at Technion - Israel Institute of Technology, Haifa. His research spans multiple areas of programming languages, formal methods, and software engineering, with a focus on making program development and verification more accessible and efficient. He has served on program committees for numerous prestigious conferences including PLDI, POPL, SPLASH, and ICFP. Dr. Itzhaky's research interests center around program synthesis, automated reasoning, and formal verification. His work in program synthesis explores techniques for automatically generating programs from high-level specifications, with applications in end-user programming and software development. In automated reasoning, he has made significant contributions to e-graph based reasoning, invariant inference, and property-directed verification. His research in formal methods focuses on practical applications for program verification, particularly for data structures and security properties. An analysis of his recent publications reveals a strong focus on leveraging advanced formal techniques for practical program understanding and generation. His work consistently bridges theoretical foundations with practical applications, particularly in program synthesis, verification, and end-user programming tools. The trend shows increasing integration of machine learning techniques with traditional formal methods, as well as expanding applications to security and privacy domains. ACM SIGPLAN John C. Reynolds Doctoral Dissertation Award Dr. Itzhaky has been actively involved in the programming languages research community, serving on numerous program committees and contributing to the advancement of formal methods and program synthesis. His work has practical implications for software development tools, security analysis, and end-user programming environments. While specific grant information isn't detailed in the provided text, his extensive publication record in top-tier venues suggests successful funding for his research endeavors. His work on projects like Object Spreadsheets and Lifty demonstrates a commitment to creating practical tools that address real-world programming challenges. Dr. Itzhaky's research is conducted within the vibrant programming languages and formal methods group at Technion's Computer Science department. His work intersects with multiple research threads including program synthesis, verification, and security, suggesting collaboration across these areas within the department. His tools like EPR-based Verification, PDR∀, and VeriCon represent significant technical contributions that likely form the basis of ongoing research projects with students and collaborators.
