Find Academic Supervisors

• Applied Financial Economics
• Economics of Security
• Financial Risk Management
• +3 more

Konstantinos Drakos is a Professor at the Department of Accounting and Finance, Athens University of Economics and Business (AUEB). Previously, he served as Assistant Professor at AUEB (2009–2012), Assistant Professor at the University of Patras (2003–2008), and Lecturer at the University of Essex (2001–2002). He holds a PhD in Economics from the University of Essex, preceded by an MSc and undergraduate studies in Economics at the University of Athens. His research focuses on Applied Financial Economics and the Economics of Security, with recent work analyzing hedge fund leverage, geopolitical risk impacts, cryptocurrency markets, and green banking. Teaching responsibilities include Macroeconomic Theory, Finance for Banking, and Risk Management at both undergraduate and postgraduate levels. Drakos' publications span over two decades, addressing topics such as terrorism's economic effects, bank lending behavior, and investment under uncertainty. His recent articles (2022–2025) emphasize cryptocurrency dynamics, geopolitical risk interactions, and financial stability in green banking. Notable themes include market volatility, capital allocation under uncertainty, and policy responses to systemic risks. No scientific awards are listed in the provided materials. His research has explored structural shifts in financial risk, macroeconomic sentiment, and cross-market linkages following major global events like 9/11 and the 2008 crisis. Drakos has advised on policy-related topics related to financial markets and regulatory frameworks, though specific grants or lab affiliations are not detailed here.

• Artificial Intelligence
• Machine Learning
• Knowledge Representation
• +7 more

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).

• Global Strategy
• Corporate Governance
• Human Resource Management
• +5 more

Jordan Siegel is a Professor of Strategy at the Ross School of Business, University of Michigan, and a Michael R. and Mary Kay Hallman Faculty Fellow. He also serves as a Visiting Faculty member at The American College of Greece (ACG). His academic background includes a Ph.D. from MIT, and B.A. and M.A. degrees from Yale University. Professor Siegel’s research focuses on global strategy, particularly how companies leverage institutional differences across borders to gain competitive advantages through governance and human resource management strategies. His work examines institutional arbitrage—how firms exploit formal and informal rules (e.g., laws, cultural norms) to enhance performance, even in single-country operations. Notably, he investigates how foreign multinationals in Japan and South Korea exploit social biases by promoting female managers, leading to long-term performance improvements. His findings highlight the strategic use of labor market discrimination as a competitive tool. Professor Siegel’s research has been published in top-tier journals such as Management Science , Administrative Science Quarterly , and Strategic Management Journal . He is affiliated with the William Davidson Institute and Harvard Korea Institute, contributing to interdisciplinary studies on global business strategy and institutional dynamics.

Amalia FokaView profile

Assistant Professor

• Artificial Intelligence Applications in Arts
• Computer Science for Creative Practices
• Digital Interaction
• +4 more

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.

Dimitris GizopoulosView profile

Professor

• Computer Architecture
• Computer Systems
• Fault Tolerance
• +5 more

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.

• International Economics
• Maritime International Trade
• Shipping Economics
• +5 more

Polemis Dionysios serves as an Associate Professor in the Department of Maritime Studies at the University of Piraeus, Greece, within the School of Shipping and Industry. His academic profile demonstrates a strong commitment to maritime education and research in the Greek academic context, contributing to one of the Mediterranean's leading institutions for maritime studies. Professor Polemis specializes in International Economics and Maritime International Trade, with research focusing on the intersection of global trade patterns and maritime transportation systems. His scholarly work examines how geopolitical shifts, economic policy uncertainty, and market dynamics impact shipping operations, particularly in the LNG sector. His research interests span shipping economics, maritime transport economics, port management, and the geopolitical dimensions of international maritime trade routes. His publications reveal a consistent focus on analyzing market patterns, regulatory compliance, and sustainability challenges within the maritime sector. His extensive publication record, spanning from 2001 to anticipated 2025 publications, demonstrates a comprehensive understanding of the maritime sector from operational, economic, and policy perspectives. Recent work shows increasing attention to emerging technologies in shipping and the evolving geopolitical landscape affecting global trade routes, particularly regarding LNG transportation and strategic maritime chokepoints like the Suez Canal. As an academic in the Department of Maritime Studies at the University of Piraeus, Professor Polemis contributes to the educational mission of an institution with a strong tradition in maritime education, situated in Piraeus—one of the Mediterranean's most important port cities. His work bridges theoretical economic concepts with practical applications in the shipping industry, providing valuable insights for both academic and industry stakeholders.

• Decision Support Systems
• Energy Management
• Environmental Analysis
• +6 more

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.

Mohsen LesaniView profile

Associate Professor

• Reliability of software systems
• Security of software systems
• Concurrent systems
• +12 more

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.

Ioannis PanageasView profile

Assistant Professor

• Algorithmic Game Theory
• Multi-agent Reinforcement Learning
• Optimization
• +2 more

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.

Panagiotis ZervopoulosView profile

Associate Professor

• operations research
• efficiency measurements
• performance measurements
• +6 more

Panagiotis Zervopoulos is an Associate Professor at the Department of Business Organization and Administration within the School of Economics, Business and International Studies at the University of Piraeus. Previously, he served as Associate Professor and Director of the PhD Program in Business Administration at the School of Business Administration of the University of Sharjah in the UAE. His research interests focus on operations research, efficiency and performance measurements, optimization methods, and econometrics. Specifically, he specializes in developing new data envelopment analysis (DEA) techniques, Bayesian methods, parametric and non-parametric econometric models, with innovative applications across multiple disciplines. His methodological contributions have been applied in diverse fields including supply chain management, financial systems, environmental efficiency, and corporate governance. Zervopoulos has published extensively in top-tier journals such as European Journal of Operational Research, Journal of the Operational Research Society, Annals of Operations Research, Journal of Financial Stability, and Journal of Cleaner Production. His recent work (2023-2024) demonstrates continued innovation in efficiency measurement techniques, particularly in network DEA models with bias correction, environmental efficiency analysis, and systemic risk measurement. His publications show strong international collaboration patterns, frequently working with researchers from different countries and institutions. He has served as Guest Editor for journals including Socio-Economic Planning Sciences and IMA Journal of Management Mathematics, demonstrating recognition of his expertise by the academic community. Zervopoulos has held research fellowships at prestigious institutions worldwide, including Peking University (China), the London School of Economics (United Kingdom), the Academy of Athens (Greece), and the Foundation for Economic and Industrial Research (Greece). He also participates in the World Economic Survey and the Economic Expert Group of the Ifo Institute (Germany). Professionally, he has served as Senior Consultant Modeling Statistician at IRi Worldwide and as Project Manager and Expert in Quantitative Analysis and Public Sector Reform through technical support projects with the European Public Law Agency.

Ioannis EmirisView profile

Professor

• Computational Geometry
• Algebraic Algorithms
• Robotics
• +4 more

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.

• Numerical analysis
• Partial differential equations
• Fluid mechanics
• +5 more

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.

Ioannis AntoniadisView profile

Professor

• Vibration Isolation and Absorption
• Negative Stiffness Systems
• Meta-materials and Periodic Structures
• +7 more

Ioannis Antoniadis is a Professor at the School of Mechanical Engineering , National Technical University of Athens (NTUA), and serves as the Dean and Director of the Dynamics and Acoustics Laboratory (DAL) . He has held academic positions since 1982, rising through the ranks from Scientific Research Assistant to full Professor since 2012. Education: Diploma in Mechanical Engineering (NTUA, 1981), Ph.D. (NTUA, 1987) Research Focus: Vibration isolation, negative stiffness systems, smart materials, seismic protection, and energy conversion Key Projects: 25+ funded research initiatives including KDamper for seismic mitigation, TRANVIC for vehicle vibration control, and 3BUILD for 3D-printing construction systems His work has resulted in 15+ peer-reviewed publications on seismic protection devices and vibration control systems, with applications in bridges, wind turbines, and industrial equipment. He has taught courses in Dynamics and Vibrations , Noise Vibration , and Signal Processing at NTUA, while leading the Mechanical Design and Automatic Control Section .

Theodora VarvarigouView profile

Professor

• Cloud Computing
• Multimedia Content Processing
• Social Networking Technologies
• +3 more

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.

Ion AndroutsopoulosView profile

Professor

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +7 more

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.