جستجوی استاد راهنمای دانشگاهی

Hakan Altınçayمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Pattern Recognition
• +۳ مورد دیگر

Prof. Hakan Altınçay is a Full Professor in the Department of Computer Engineering at Eastern Mediterranean University (EMU). He holds a PhD from Middle East Technical University (METU), Turkey (2000), and has been at EMU since 2000, progressing from Assistant Professor (2000–2005) to Full Professor (2012–present). His research focuses on machine learning, including imbalance learning, feature selection, ensemble methods, and biomedical data analysis. He has supervised 10+ PhD and Master’s theses and authored over 50 journal and conference papers. Education: BEng in Electrical and Electronics Engineering (METU, 1993), MSc and PhD in Electrical Engineering (METU, 2000). Awards include the IEEE Third Best Paper Award (2003) and TÜBİTAK PhD Scholarship. He serves on editorial boards (e.g., Applied Intelligence Journal) and chairs academic committees at EMU. Key contributions include algorithms for imbalanced data classification (MaMiPot), feature selection techniques, and biomedical applications like diabetes prediction. His work addresses challenges in text categorization, speaker verification, and ensemble classifier design.

Sturt Manningمشاهده پروفایل

استاد

• Mediterranean Archaeology
• Dendrochronology
• Radiocarbon Dating
• +۳ مورد دیگر

Sturt Manning is a Distinguished Professor of Arts and Sciences in Classics at Cornell University and serves as Director of the Cornell Tree-Ring Laboratory. He is also an Adjunct Professor at the Cyprus Institute's Science and Technology in Archaeology and Culture Research Center (STARC). His research focuses on Mediterranean archaeology, particularly in the Aegean, Cyprus, and Eastern Mediterranean regions, with specializations in dendrochronology, radiocarbon dating, and archaeological science. Research interests include Mediterranean cultural connections, trade networks, artistic traditions, and chronological frameworks. Current projects include co-directing the Kalavasos and Maroni Built Environments Project and collaborative work on Medieval monuments in Cyprus. Recent publications demonstrate a strong focus on refining chronological methodologies, particularly through radiocarbon calibration techniques and analysis of climatic events affecting ancient civilizations. Research consistently explores the intersection of environmental change and cultural development. Laboratory leadership includes directing the Cornell Tree-Ring Laboratory, which supports archaeological dating and climate reconstruction projects through dendrochronological analysis.

• Artificial Intelligence
• Bayesian Networks
• Computer Vision
• +۵ مورد دیگر

Professor Athena Stassopoulou is a faculty member at the University of Nicosia , serving as Head of the Department of Computer Science within the School of Sciences and Engineering. Her academic journey began with a BSc in Computer Science and Mathematics from the University of Manchester (UK) and a PhD in Artificial Intelligence from the University of Surrey (UK). She has held prestigious research roles at NASA Commercial Space Center, Ohio State University, and the National Imagery and Mapping Agency (USA), focusing on machine vision algorithms and image understanding. Education : BSc (University of Manchester), PhD (University of Surrey) Research Expertise : Uncertain reasoning, Bayesian Networks, Computer Vision, Machine Learning, Medical Informatics, Geographic Information Systems Her research spans decades, integrating Temporal Abstraction and Bayesian Networks for medical diagnosis, particularly in coronary heart disease. Recent work explores Adverse Drug Reaction Classification in Social Media and Dynamic Bayesian Network Models . Funded by NASA, EU, and Cypriot agencies, she has also contributed to web crawler detection and GIS-based decision-making systems. Notable collaborations include partnerships with Ohio State University and European institutions. Her career bridges theoretical AI with practical applications in healthcare and cybersecurity.

Amr Abdelbariمشاهده پروفایل

استادیار

• Wireless Communication Systems
• Signal Processing
• 5G Networks
• +۴ مورد دیگر

Assistant Professor Amr Abdelbari is affiliated with the Data Analytics Engineering Department at Near East University. His research focuses on wireless communication systems, signal processing, and machine learning applications in telecommunications. Academic Rank: Assistant Professor University: Near East University Department: Data Analytics Engineering Research interests include: Massive MIMO and 5G network optimization Direction-of-Arrival (DOA) estimation techniques Machine learning for wireless communication IoT applications in civil engineering Probabilistic and fuzzy logic-based signal processing Recent publications (2020-2025) demonstrate expertise in wideband signal processing, NOMA systems, and error probability modeling. Key trends in his work include integrating fuzzy logic for network optimization, improving DOA estimation for 5G systems, and applying neural networks to renewable energy modeling. Contact: amr.abdelbari@neu.edu.tr

Yiolanda Englezouمشاهده پروفایل

پژوهشگر ارشد

• Bayesian Estimation
• Probabilistic Forecasting
• Uncertainty Quantification
• +۳ مورد دیگر

Yiolanda Englezou is a Senior Research Associate at the KIOS Research and Innovation Centre of Excellence, University of Cyprus. She holds a PhD from the University of Southampton and specializes in Bayesian estimation, probabilistic forecasting, and uncertainty quantification for dynamic systems. Research applications focus on intelligent transportation systems including traffic density estimation using UAV data, origin-destination matrix estimation, and sensor fault detection. Methodologies integrate Bayesian statistics with machine learning techniques for transportation network optimization.

Joseph Josephمشاهده پروفایل

استاد بالینی

• Cardiology
• Rheumatology
• Epidemiology of Rheumatic Diseases
• +۴ مورد دیگر

Joseph Joseph serves as Clinical Professor, Associate Dean of Academic Affairs, and Chair of Clinical Education at the University of Nicosia Medical School. He graduated with an MB BCh from the University of Wales College of Medicine and specialized in Internal Medicine and Rheumatology at Oxford University. His clinical focus includes rheumatic disease epidemiology, inflammatory arthritis, and Behcet’s Disease. His research spans cardiology, diabetes management, and cardiovascular risk assessment, with notable contributions to biomarker studies in COVID-19 patients and algorithmic approaches to coronary heart disease risk. Education: MB BCh, University of Wales College of Medicine (UK) Specialization in Internal Medicine and Rheumatology, Oxford University Research Interests: Dr. Joseph’s work emphasizes translational cardiology, including the intersection of metabolic disorders (diabetes, obesity) with cardiovascular disease. He is particularly interested in developing predictive models for adverse cardiac events and innovative therapeutic approaches for rheumatic conditions. His cross-disciplinary projects integrate clinical informatics with traditional medical research. Publications Trends: His articles reflect a focus on cardiovascular epidemiology, biomarker discovery, and the application of data science in medicine. Recent work explores the impact of comorbidities like diabetes and hypertension on coronary artery disease outcomes, while earlier studies investigate ischemic preconditioning and endovascular techniques. Awards: No scientific awards explicitly listed in the profile. Advising & Grants: No advisees or grant details provided in available texts. His administrative roles suggest involvement in academic program development rather than active research grants. Labs/Teams: Not explicitly mentioned, though his role as Chair of Clinical Education implies leadership in educational infrastructure development within the medical school.

Nikolaos Tsakasمشاهده پروفایل

دانشیار

• Microeconomic Theory
• Information Economics
• Political Economy
• +۳ مورد دیگر

Nikolaos Tsakas is an Associate Professor at the Department of Economics, University of Cyprus, and a founding member of UCY LExEcon (Laboratory for Experimental Economics). He joined UCY in 2015 as a Lecturer, was promoted to Assistant Professor in 2019, and to Associate Professor in 2024. Previously, he held a postdoctoral position at the SUTD-MIT International Design Center in Singapore (2014-2015). He holds a PhD in Economics from Universidad Carlos III de Madrid (2011-2014), a Master's in Economic Analysis from the same institution (2009-2011), and a Bachelor's in Civil Engineering from the University of Patras (2004-2009). His research focuses on Microeconomic Theory , Information Economics , Political Economy , Experimental Economics , Social Networks , and Industrial Organization . He employs game-theoretic modeling and laboratory experiments to study communication, voting systems, persuasion mechanisms, and network dynamics. Analysis of his 15 most recent publications (2015-2025) reveals consistent themes: experimental validation of game-theoretic models, information aggregation in voting systems, strategic communication under uncertainty, and network-based behavioral diffusion. His work frequently appears in top-tier journals including Journal of European Economic Association , Games and Economic Behavior , and Journal of Economic Theory . At UCY LExEcon, he contributes to experimental research infrastructure and collaborative projects. His teaching portfolio includes graduate and undergraduate courses such as: ECONOMY251: Microeconomics Topics ECO324: Introduction to Political Economy and Public Policy ECO651: Microeconomic Analysis II ECO415: Game Theory (previously taught)

Panayiotis Christodoulouمشاهده پروفایل

دانشگاهی

• Recommender Systems
• Blockchain Technologies
• IoT
• +۷ مورد دیگر

Panayiotis Christodoulou is a Visiting Lecturer of Computer Science at the Department of Computer Science, Neapolis University Pafos. He holds a PhD in Computer Engineering and Informatics from Cyprus University of Technology (CUT) and completed undergraduate and postgraduate studies at Manchester University (UK) and Frederick University (Cyprus). His research focuses on Recommender Systems, Blockchain technologies, IoT, and Smart Cities, with notable contributions to EU projects like DOSSIER-Cloud, SmartGov, and INNOLABS. Education Background: PhD in Computer Engineering and Informatics, Cyprus University of Technology (CUT) MEng in Engineering, Manchester University, UK MSc in [unspecified field], Frederick University, Cyprus Research Interests: His work spans blockchain applications in finance (e.g., Green Bonds), IoT data management, cybersecurity for decentralized systems, and educational robotics. He pioneered frameworks like DLMetaChain (IoT blockchain data lake) and Skillschain (blockchain-robotics education platform). His recent studies address greenwashing detection, smart city citizen perceptions, and pandemic-era healthcare data challenges. Professional Contributions: Panayiotis has managed multiple EU-funded projects, demonstrating expertise in project leadership and innovation. He is affiliated with CUT's Software Engineering and Intelligent Information Systems Research Lab, contributing to cutting-edge R&D in complex event processing and real-time recommendation systems. Labs & Teams: Active member of the Software Engineering and Intelligent Information Systems Research Lab at CUT, collaborating on projects integrating blockchain with IoT, AI, and educational technologies.

Petr Hájekمشاهده پروفایل

استاد

• Machine Learning
• Neural Networks
• Fuzzy Logic
• +۷ مورد دیگر

Petr Hájek is a Professor at the University of Pardubice in the Institute of System Engineering and Informatics, Czech Republic. With 236 publications, 71,463 reads, and 5,595 citations, he has established himself as a prominent researcher in computational intelligence and machine learning applications. His research interests span multiple domains of computational intelligence, with particular focus on: Machine learning applications in financial forecasting and risk management Neural networks and fuzzy logic systems for time series prediction Sentiment analysis for financial markets and social media Fraud detection and fake news identification systems Cryptocurrency price forecasting and market analysis ESG analytics and sustainable finance applications Analysis of his recent publications (2023-2025) reveals an expanding research scope that increasingly integrates sustainability considerations with financial technology. His work demonstrates sophisticated methodological approaches, frequently employing hybrid neural network architectures, ensemble learning techniques, and advanced text mining methods. Professor Hájek's research shows strong international collaboration patterns with scholars across Europe, Asia, and North America. His scholarly contributions have focused on developing practical AI solutions for complex financial problems, with particular attention to handling class imbalance issues in financial datasets and creating interpretable models for financial decision-making. Professor Hájek maintains an active research program with consistent publication output across top venues in computational intelligence and financial technology. His work bridges theoretical advances in machine learning with practical applications in finance, demonstrating both academic rigor and real-world relevance.