جست‌وجوی استاد و پژوهشگر

Angelos Kanasمشاهده پروفایل

استاد

• Finance
• International Finance
• Financial Markets
• +۲ مورد دیگر

Angelos Kanas is a Professor of Finance at the Department of Economics within the School of Economics, Business and International Studies at the University of Piraeus. His academic career spans over two decades with significant contributions to finance, banking, and econometric modeling, supported by continuous research funding from entities including NATO and the European Union. His educational background includes undergraduate studies funded by the Hellenic National Scholarships Foundation (I.K.Y.), an M.Sc. supported by the Bodosakis Foundation, and a Ph.D. financed by the National Scholarships Foundation (I.K.Y.). Kanas specializes in Finance, International Finance, Financial Markets, Financial Risks and Protection, and Banking. His research integrates advanced quantitative methods to analyze systemic risk, market efficiency, and policy impacts, with particular focus on regime-switching models and DEA efficiency measurements. Recent work explores intersections between climate finance, banking stability, and corporate governance. Analysis of his 15 most recent publications reveals an evolving research trajectory: early work (2005-2013) established expertise in exchange rate dynamics and asset pricing, while post-2015 research increasingly addresses banking regulation, systemic risk prediction, and methodological innovations in efficiency analysis. Current work (2022-2025) demonstrates strong engagement with climate-related financial risks and AI applications in finance. Hellenic National Scholarships Foundation (I.K.Y) studentship (undergraduate, three annual) Bodosakis Foundation scholarship (M.Sc.) National Scholarships Foundation (I.K.Y.) scholarship (Ph.D.) Kanas has secured research funding from NATO and EU bodies, reflecting recognition of his work's policy relevance. His extensive refereeing activities across 30+ journals including Journal of International Economics and Journal of Banking and Finance demonstrate scholarly leadership. He teaches core finance courses including International Finance and Special Topics in Finance, and has authored two academic books: Principles of Investment Analysis and Financial Markets (2021) and FinTech and Machine Learning: Basic Principles and Applications (2023).

Angelos Alexopoulosمشاهده پروفایل

استادیار

• Theoretical and Applied Econometrics
• Bayesian Analysis
• Computational Statistics
• +۴ مورد دیگر

Angelos Alexopoulos is an Assistant Professor at the Department of Economics , Athens University of Economics and Business . He has held Research Associate positions at the University of Cambridge, University College London, and University of Exeter in the UK. PhD: Athens University of Economics and Business Research Focus: Computational Statistics, Econometrics, Bayesian Analysis, Network Modelling Publications span Bayesian inference, epidemic forecasting, machine learning for fraud detection, and econometric methodology. Key journals include Journal of the Royal Statistical Society , Journal of Computational and Graphical Statistics , and Statistics and Computing . 2024: Gaussian invariance in MCMC 2024: Epidemic nowcasting models 2023: VAT fraud detection with ML Awards include certifications in Deep Learning (Coursera), Blockchain (edX), and Object-Oriented R Programming (DataCamp).

Dimitrios Karolidisمشاهده پروفایل

مدرس

• Web Application Development
• Geographic Information Systems
• Educational Technology
• +۵ مورد دیگر

Dimitrios Karolidis is a Lecturer at the Department of Informatics and Computer Engineering within the School of Engineering at the University of West Attica (UniWA). He holds a Bachelor's degree in Physics from the University of Ioannina and a Master's in New Information and Communication Technologies from the National and Kapodistrian University of Athens (NKUA). Education: BSc in Physics, University of Ioannina MSc in New Information and Communication Technologies, NKUA His research focuses on Web Application Development , Internet Technologies , and Machine Learning . He has contributed to photovoltaic system optimization through projects like SmartPV , emphasizing fault detection, energy efficiency, and IoT integration. His publications highlight advancements in smart photovoltaic systems , including fault detection algorithms and communication protocols, aiming to reduce maintenance costs and improve energy output. He has also authored textbooks on programming languages like C and Python, widely used in academic settings. He has previously held academic positions at the Technological Educational Institute of Athens (2007-2018) and TEI Piraeus , working on laboratory and teaching roles related to computer systems and networks.

Sergios Dimitriadisمشاهده پروفایل

استاد

• Digital Marketing
• Consumer Behavior
• Brand Management
• +۳ مورد دیگر

Sergios Dimitriadis serves as Professor in the Department of Marketing and Communication at Athens University of Economics and Business (AUEB), where he has taught since 2000 following ten years of academic and consulting experience in France. His instructional portfolio includes Digital and Omni-channel Marketing, Customer Experience Management, and Digital Content courses. His educational credentials feature a foundational degree from Athens University of Economics and Business and a doctoral degree from France's University of Aix-Marseille. Professor Dimitriadis specializes in digital consumer behavior with emphases on social media brand dynamics, 3D virtual retail environments, and relational value frameworks. His research investigates how technological interfaces shape consumer-brand interactions, particularly examining perceived value constructs in Facebook ecosystems and spatial navigation in immersive online stores. Analysis of his 15 most recent publications reveals consistent focus on relational benefit-cost dynamics across digital contexts, with methodological strengths in experimental design and multivariate analysis. Key thematic trajectories include green brand relationship metrics (2018-2019), social media brand page typologies (2018), and trust-based segmentation in financial technology (2011). No scientific awards were documented in source materials. As scientific director of AUEB's Center for Training and Lifelong Learning educational programs, he bridges academic and professional spheres through European/national research program consultancy and organizational training initiatives, demonstrating commitment to applied knowledge transfer despite absence of specific grant details.

Giota Touloumiمشاهده پروفایل

استاد

• Biostatistics
• Epidemiology
• Infectious Diseases
• +۴ مورد دیگر

Giota Touloumi is Professor of Biostatistics and Epidemiology at the Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens (NKUA). She directs the interdepartmental MSc on Biostatistics and Health Data Science and teaches undergraduate courses in Biostatistics (Medical/Dentistry/Biology programs) and postgraduate courses including Generalized Linear Models. Her academic background includes an MSc in Biostatistics and PhD from London School of Hygiene & Tropical Medicine, and a doctoral thesis in Epidemiology/Medical Statistics from NKUA. Her research spans: Development of novel statistical methods for health data analysis Infectious disease epidemiology (HIV, hepatitis B/C) Chronic disease risk factors (cardiovascular focus) Clinical trials for infectious diseases including COVID-19 Public health surveillance and environmental epidemiology She leads multiple national/international studies including AMACS (HIV cohort), EMENO (national health survey), Hprolipsis (viral hepatitis/HIV screening), and Hippocrates Epidemic Detection System. Through INSIGHT network, she coordinates NIH-funded COVID-19 therapeutic trials in Greece. Publication analysis reveals strong focus on: Infectious disease dynamics (HIV/HCV co-infections, COVID-19) Statistical methodology for longitudinal/clustered data National health surveys (cardiovascular risks, diabetes, vaccination attitudes) Global burden of disease collaborations (NCD-RisC) Clinical trial design for pandemic response She coordinates significant research infrastructure as Principal Investigator for: HEPNET.Greece statistical/data center (10+ years) EU/ECDC/NIH-funded multinational studies INSIGHT network clinical trials in Greece and participates in international consortia including ART-CC, HIV-CAUSAL, CASCADE, and NCD-RisC.

Garofalakis Minosمشاهده پروفایل

استاد

• Database Systems
• Data Streams
• Big Data Analytics
• +۷ مورد دیگر

Minos Garofalakis is a Professor of Computer Science at the School of Electrical and Computer Engineering (ECE) of the Technical University of Crete (TUC), where he directs the Software Technology and Network Applications Laboratory (SoftNet). He is also the Director of the Information Management Systems Institute (IMSI) at the Athena Research and Innovation Centre in Athens. Previously, he held roles at Yahoo! Research, Intel Research Berkeley, and Bell Laboratories, and was an Adjunct Associate Professor at UC Berkeley. Education: He earned a BSc in Computer Engineering from the University of Patras (1992), followed by MSc (1994) and PhD (1998) in Computer Science from the University of Wisconsin-Madison. Research Interests: His work focuses on Big Data analytics , including database systems, data streams, approximate query processing, probabilistic databases, and secure/private data analytics. Key areas include distributed stream processing, data synopses, and machine learning applications. He has authored over 150 papers and holds 29 patents, with an h-index of 63 and 13,500+ citations. Recent Work Trends: His recent articles emphasize scalable stream analytics (e.g., OmniSketch), privacy-preserving techniques, and distributed event processing. He explores challenges in handling high-velocity data streams, uncertainty in databases, and real-world applications like healthcare analytics. Scientific Awards: ACM Fellow (2018), IEEE Fellow (2017), TUC Excellence Award (2015), and multiple patents from Bell Labs/Yahoo/AT&T. Advising & Grants: He led EU projects such as FERARI, LEADS, and The Human Brain Project. His lab, SoftNet, develops tools for extreme-scale analytics and declarative networking. Current work includes interactive cross-platform analytics (Infore) and AI-driven medical data systems. Labs/Teams: Director of SoftNet Lab and IMSI. Collaborates with industry partners on distributed systems and privacy-preserving technologies.

• Information Processing over Networks
• Adaptive Signal Processing & Learning
• Statistical Learning
• +۴ مورد دیگر

Berberidis Kostas is a Professor at the University of Patras, Department of Computer Engineering and Informatics. His academic work focuses on Information Processing over Networks , Adaptive Signal Processing , and Wireless Communications . He is affiliated with the Division of Hardware and Computer Architecture. Specialized in Statistical Learning and Distributed Information Processing Contributed to advancements in Signal Processing for Communications and Array Signal Processing Notable research areas include: Adaptive and distributed learning algorithms Wireless channel equalization and relaying Hyperspectral and biomedical image processing Resource allocation with security constraints Recent publications cover topics like blind hyperspectral unmixing , secure resource allocation , and FIR filter optimization , reflecting his interdisciplinary focus on signal processing, communications, and computational imaging.

Tsichlas Kostasمشاهده پروفایل

دانشیار

• Algorithms and Data Structures for Main and Secondary Memory
• Algorithms and Data Structures in Distributed Environments
• Computational Geometry
• +۵ مورد دیگر

Tsichlas Kostas serves as an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece, within the Division of Applications and Foundations of Computer Science. His research spans fundamental and applied computing domains with active involvement in the ML@Cloud laboratory. His expertise centers on algorithmic innovation across multiple dimensions: Memory-optimized algorithms for primary/secondary storage systems Distributed environment data structures and computational geometry Physics-informed computing and complex network analysis Specialized domains including alphanumeric and graph algorithms Recent publication trends (2022-2025) demonstrate concentrated research in historical graph management systems, temporal network analysis, and physics-computing intersections. Key contributions include vertex-centric partitioning strategies, temporal community detection frameworks, and machine learning applications for energy data motif discovery. He maintains active laboratory affiliations with the LARGE-SCALE CLOUD DATA MACHINE LEARNING WORKSHOP (ML@Cloud lab), Combinatorial Algorithms Laboratory, and Distributed Systems and Telematics Laboratory, contributing to Greece's computational research infrastructure.

• Data Science
• Data Mining
• Big Data Analytics
• +۸ مورد دیگر

Nikolaos Pelekis is a Professor at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus, where he teaches courses in Data Science, Data Management, Information Systems, and Computer Programming. He has been actively involved in both undergraduate and postgraduate education, offering specialized courses such as "Statistical Data Mining Methods" in the Applied Statistics Master's program and "Big Data Management" in the Cybersecurity and Data Science postgraduate program. Born in 1975, Professor Pelekis earned his Bachelor's degree in Computer Science from the University of Crete (1998), followed by an MSc in Information Systems Engineering (1999) and a PhD in Moving Object Databases (2002) from UMIST University in the United Kingdom. His educational background laid the foundation for his distinguished career in data science and database management. Professor Pelekis' research spans multiple domains within data science and database management, with particular emphasis on mobility data analytics. His work focuses on data mining, big data management and analytics, with special attention to location and motion data including trajectories of moving objects. He has made significant contributions to spatial and spatiotemporal database management, moving object database systems, privacy-preserving data mining, and OLAP analysis. His research bridges theoretical foundations with practical applications, particularly in maritime and transportation domains. An analysis of Professor Pelekis' recent publications reveals a strong trend toward maritime data analytics and vessel traffic prediction. His work increasingly focuses on applying machine learning techniques to maritime trajectory data, developing systems for collision risk assessment, vessel location forecasting, and maritime route prediction. The research demonstrates a progression from foundational database management techniques to sophisticated analytics for time-critical mobility forecasting, with applications in aviation and maritime domains. Five best research paper awards 1st & 3rd place in the SemEval-2017 competition 3rd place in the ACM SIGSPATIAL Cup 2016 competition Best paper award at ACM SIGSPATIAL'14 (Path-based Queries on Trajectory Data) Best paper award at ER'13 (Baquara: A Holistic Ontological Framework for Movement Analysis with Linked Data) Best application paper award at ICDM'09 (Clustering Trajectories of Moving Objects in an Uncertain World) Ralf H. Güting best research paper award at SSTD'21 (A Novel Indexing Method for Spatial-Keyword Range Queries) Best Demo Paper award at SSTD'21 (MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories) Professor Pelekis has been actively involved in advising and research funding acquisition. He has participated in over 10 European and National Research and Development projects as principal investigator or key researcher. His leadership extends to directing research laboratories and coordinating large-scale collaborative projects. As co-founder of the Data Science Lab - DataStories at the University of Piraeus, he has mentored numerous researchers and students. His research has been supported by prestigious funding programs including Horizon Europe, Horizon 2020, and national research initiatives. Professor Pelekis co-founded and leads the Data Science Lab - DataStories at the University of Piraeus, which comprises 9 faculty members from 4 different Departments along with experienced and young researchers. He previously served as Head of Research for the Information Management Lab (InfoLab) at the Department of Informatics, University of Piraeus (2005-2014). His current research team is actively engaged in multiple European projects including "DAT.AI – Energy-efficient AI-ready Data Spaces" and "EMERALDS – Extreme-scale Urban Mobility Data Analytics as a Service," focusing on cutting-edge applications of data science in maritime and urban mobility contexts.

Rachaniotis Nikolaosمشاهده پروفایل

دانشیار

• Supply Chain Management
• Industrial Management
• Technology
• +۳ مورد دیگر

Rachaniotis Nikolaos is an Associate Professor at the Department of Industrial Management and Technology , School of Shipping and Industry , University of Piraeus . He has been active in research and teaching since at least 2023, with a focus on supply chain management, logistics, and technology applications in industrial contexts. Research Interests include: Supply Chain Digitalization Blockchain Applications in Logistics Sustainable Public Procurement Data Analytics in Operations Epidemic Control Modeling Fuel Supply Chain Optimization Recent Articles (2023–2025) demonstrate expertise in: Supply Chain Technology (Blockchain, eFTI regulation) Sustainability Metrics (Life Cycle Costing, Green Procurement) Pandemic Response Logistics (COVID-19, Smallpox) Advanced Data Analysis (k-NN algorithms, Stochastic Modeling) Contact : nraxan@unipi.gr

• Social Insurance
• Insurance Economics
• Economics of Aging
• +۷ مورد دیگر

Platon Tinios is a Professor in the Department of Statistics and Actuarial Science at the University of Piraeus, Greece. An economist by training, he completed his education at prestigious UK institutions including Cambridge (BA, PhD) and Oxford (MPhil). His academic journey began at Christ's College, Cambridge University (1975-1978) for his BA in Economics, followed by Nuffield College, Oxford University (1978-1980) for his MPhil, and returned to Christ's College, Cambridge University (1980-1984) for his PhD with a thesis titled "Housing Demand and Taxation in Greece: An Econometric Analysis of the Household Expenditure Survey, 1974". Professor Tinios has held influential positions including Advisor to the Prime Minister of Greece (1996-2004) with a special focus on economic aspects of social policy, and membership in the European Union's Social Protection Committee (1999-2004). He was the main author of the Sprouse Report on pensions in 1997 and has been involved in numerous international research collaborations including Horizon 2020 projects and World Bank initiatives. His research expertise spans social insurance, the economics of aging, social policy economics, public finances, and gender economics. His scholarly output is extensive and influential, with numerous publications addressing pension systems, particularly in the context of Greece's economic challenges. His work examines three-pillar pensions as potential levers for growth recovery, as documented in his 2018 book "Pensions for Young People" (co-authored with M. Nektarios and G. Symeonidis). Recent publications focus on long-term care systems, financial risk attitudes among aging populations, and pandemic response strategies, reflecting his ability to address contemporary challenges through rigorous economic analysis. Professor Tinios has been actively involved in significant research projects including serving as Scientific Responsible in Greece for SHARE-COVID 19 (Horizon 2020 project, 2020-2024), Consultant for the World Bank research project "The reform of Social Care Services in Greece" (2020-2021), and Deputy Scientific Coordinator of the Greek group in the multinational "Survey of Health and Retirement in Europe" (SHARE) since 2002. His participation in the SPRINT project (2015-2018) and UK Economic and Social Research Council projects further demonstrates his international research profile. As an educator, Professor Tinios teaches undergraduate courses in Social Insurance, Insurance Economics, Macroeconomics, and Population Aging and Insurance Economics, as well as postgraduate courses on Pension schemes and social security. His teaching reflects his commitment to connecting theoretical economic principles with practical policy applications, preparing students to address real-world challenges in economics and social policy, particularly in the context of aging populations and social security systems.

Earl T. Barrمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Type Systems
• +۶ مورد دیگر

Earl T. Barr is a Professor of Software Engineering at University College London (UCL), where he heads the System Software Engineering Group and is a member of the Centre for Research on Evolution, Search and Testing (CREST). His academic journey began with a Ph.D. in Computer Science from the University of California, Davis in 2009, after which he joined UCL as faculty. His research spans multiple domains within software engineering, with particular focus on program analysis, type systems, automated program repair, and the emerging field of dual channel analysis that examines the interplay between natural language and formal programming language in source code. Barr's work on the 'naturalness of software' has been influential in understanding how code differs from natural language while exhibiting statistical regularities. Barr's publication record shows a strong trend toward integrating machine learning with traditional software engineering techniques, particularly in type inference (Typilus), program repair, and code understanding. His recent work increasingly focuses on dual channel analysis, exploring how the natural language elements in code (identifiers, comments) interact with the formal programming language to create a richer communication channel for developers. MSR 2019 Most Influential Paper Award Multiple ACM SIGSOFT Distinguished Paper Awards Best Paper Award at IEEE Conference on E-Commerce Technology (2005) Barr actively supervises numerous Ph.D. students and postdocs, with current projects focusing on dual channel program analysis, AI for code, and software security applications. He has established long-term collaborations with researchers at institutions including Royal Holloway and the University of Luxembourg. His teaching portfolio at UCL includes core courses in Malware, Compilers, and Validation and Verification, reflecting his broad expertise across the software engineering spectrum. Barr leads the System Software Engineering Group at UCL, which focuses on practical applications of software engineering research with strong connections to industry problems. The group's work bridges theoretical foundations with real-world software development challenges, particularly in the areas of program analysis and automated software maintenance.

Petros Varthalitisمشاهده پروفایل

استادیار

• Macroeconomics
• Fiscal Policy
• Monetary Policy
• +۵ مورد دیگر

Petros Varthalitis serves as an Assistant Professor in the Department of Economics within the School of Economic Sciences at Athens University of Economics and Business (AUEB). His academic trajectory includes significant roles at the Economic and Social Research Institute (Ireland), University of Glasgow, and Scottish Fiscal Commission, complemented by a visiting scholar position at the Central Bank of Greece. His institutional affiliations demonstrate deep engagement with European fiscal policy institutions and central banking frameworks. Dr. Varthalitis specializes in theoretical and applied macroeconomics, with concentrated expertise in fiscal and monetary policy analysis using Dynamic Stochastic General Equilibrium (DSGE) models for both open and closed economies. His research portfolio critically examines fiscal and currency unions, debt consolidation mechanisms, and structural reforms in public finance. Methodologically, he integrates advanced modeling techniques including Heterogeneous Agent New Keynesian (HANK) frameworks and machine learning applications to address contemporary economic challenges. Analysis of his 15 most recent publications (2020-2025) reveals three dominant research clusters: Euro Area fiscal architecture (debt sustainability, HANK modeling, fiscal spillovers), crisis response economics (comparative analysis of Global Financial Crisis and COVID-19 impacts, intangible investment dynamics), and methodological innovations (machine learning for economic data construction, asymmetric link functions in risk modeling). His work consistently bridges academic rigor with policy relevance, particularly regarding fiscal policy design in monetary unions. Dr. Varthalitis maintains active contributions to policy institutions including the Economic and Social Research Institute and Scottish Fiscal Commission. His scholarly output appears in premier journals such as Journal of Economic Dynamics and Control and International Journal of Central Banking, alongside authoritative edited volumes from Cambridge University Press and MIT Press. While his research demonstrates significant policy impact, specific grant funding details and student mentorship activities are not documented in the available materials.

• Machine Learning
• Intelligent Agents
• Computer Vision
• +۴ مورد دیگر

Konstantinos Blekas is a Professor at the Department of Computer Engineering and Informatics, University of Ioannina, Greece. He is affiliated with the Polytechnic School and teaches advanced courses such as 'Machine Learning' (MYE002) and 'Probability and Statistics' (MYY304). His research focuses on Machine Learning, Intelligent Agents, Computer Vision, and Bioinformatics, with particular expertise in Reinforcement Learning, Deep Learning, and their applications in autonomous systems, traffic management, and aerospace engineering. Education: Ph.D. in Electrical and Computer Engineering, National Technical University of Athens (1997) Diploma in Electrical Engineering, National Technical University of Athens (1993) Research Interests: Dr. Blekas explores cutting-edge topics in machine learning, including generative adversarial networks (GANs), multi-agent systems, and reinforcement learning for autonomous navigation. His work spans domains such as unmanned surface vehicles, air traffic management, and medical informatics. Notable contributions include advanced frameworks for flight trajectory modeling, urban traffic optimization, and brain functional network analysis. Awards and Recognition: While specific awards are not explicitly listed, his extensive publications and contributions to AI and robotics reflect significant academic impact. Advising and Grants: He supervises research in machine learning applications, though specific student names or grant details are not provided in the texts. His courses emphasize practical implementation, with resources available on e-learning platforms like e-course.uoi.gr. Labs and Teams: Engaged in collaborative projects involving robotics and AI, though no specific lab names are mentioned. His work integrates interdisciplinary approaches across computer science, engineering, and biomedical fields.

• Data Warehousing
• OLAP
• Data Mining
• +۵ مورد دیگر

Ioannis Kotidis is an Associate Professor in the Department of Informatics at the Athens University of Economics and Business (AUEB), School of Information Sciences and Technology. He holds a Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens (1995), and Master's and Ph.D. degrees from the University of Maryland (1997, 2000). Prior to joining AUEB, he worked as a Senior Technical Specialist at AT&T Labs-Research in Florham Park, New Jersey until January 2006. His research spans multiple areas of database systems with particular focus on On-Line Analytical Processing (OLAP) and data warehousing, data mining, sensor/P2P networks, mobile data management, data fusion & dissemination, data streams, RFID data management, approximate query answering, and database preservation . His work bridges theoretical foundations with practical implementations, as evidenced by numerous publications in top-tier database conferences and journals. Professor Kotidis leads several significant research projects including RECOST (REal time management of COmplex STreams), DBSENSE (Information Management in Wireless Sensor Networks), INFORE (Interactive Extreme-Scale Analytics and Forecasting), and DeLorean (Storage, Indexing and Analysis Techniques for Time-Series Management). His recent work focuses on blockchain applications for decentralized OLAP processing, complex event processing frameworks, and advanced techniques for managing complex data streams. Among his notable achievements is the best paper award at the ACM SIGMOD International Conference on Management of Data for his work on DynaMat: A Dynamic View Management System for Data Warehouses. His publications consistently address challenging problems in database systems with innovative approaches that have influenced both academic research and practical implementations. He has supervised numerous undergraduate theses on topics including blockchain-based OLAP view management, complex event processing using FlinkCEP, and graph similarity learning. His research has attracted significant funding through various research programs at AUEB, including Basic Research Funding Programs 1 & 2.