Konstantinos A. Dimitriadis is an Assistant Professor at Mesoyios Academy with a multidisciplinary background in Finance, Economics, and Quantitative Methods. He holds a Ph.D. in Finance and Economics, an M.Sc. in Shipping and Finance, and a B.Sc. in Mathematics and Statistics. Contact: Email: kdimitriadis@mesoyios.ac.cy, mcrc@mesoyios.ac.cy | Phone: +357 25 246408 His academic profile combines financial economics with mathematical rigor, enabling research at the intersection of capital markets, quantitative finance, and maritime economics. While specific publications and awards aren't listed, his educational foundation suggests analytical approaches to financial systems and risk modeling.
OlaOluwa Simon Yaya is an Associate Professor at the University of Ibadan Department of Statistics, with additional appointments as University Professor at Global Humanistic University Curacao and Research Fellow at the Centre for Econometrics and Applied Research Nigeria. He is affiliated with the University of Ibadan Laboratory for Interdisciplinary Statistical Analysis. Professor Yaya holds a B.Sc. from Abeokuta, and M.Sc. and PhD from Ibadan. His academic journey has led him to become a recognized expert in time series econometrics and related fields. Professor Yaya specializes in Economic and Financial Time Series, Climate Change modelling, Time Series Econometrics, Machine Learning/Big Data and Pattern Recognition. His research particularly focuses on Dynamic connectedness, Fractional integrated processes, Fractional Cointegration, Panel Unit root tests, Structural breaks, Seasonality, and Nonlinearities in the context of I(d) models. He also works extensively on Volatility modelling in both univariate and multivariate settings, including Realized Volatility with Jumps. His recent publications (2024-2025) demonstrate continued research activity across multiple domains including financial markets, climate change, energy economics, public health, and economic policy. These works show a strong emphasis on advanced time series methodologies applied to real-world problems, with particular attention to persistence properties and connectedness across different economic and financial variables. Professor Adenike Osofisan Faculty of Science Scholar Award (2019) 232 publications with 49,175 reads and 2,029 citations As an advisor and educator, Professor Yaya has supervised numerous research projects and publications. His international collaborations span multiple continents, working with researchers from Portugal, Vietnam, Spain, and across Africa, Europe, and Asia. His research group focuses on developing and applying advanced statistical methodologies to solve complex problems in economics, finance, climate science, and public policy. Professor Yaya leads research activities at the University of Ibadan Laboratory for Interdisciplinary Statistical Analysis, where his team applies cutting-edge time series techniques to diverse research questions across multiple disciplines, bridging theoretical methodology with practical applications in economic and social challenges.
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.
Dr Theodosis Mourouzis serves as an Assistant Professor of Information Management at the University of Nicosia and directs the MSc in Business Intelligence and Data Analytics program within the Department of Information Technologies. Academic Background: PhD in Information Security and Cryptography from University College London (UCL) MSc in Advanced Studies in Mathematics from University of Cambridge BA/MA in Mathematics from University of Cambridge Research Expertise: Dr Mourouzis specializes in information security with deep technical focus on cryptography (including symmetric/asymmetric cryptanalysis) and blockchain ecosystems . His work spans theoretical cryptanalysis of algorithms like GOST and SIMON to practical implementations such as privacy-preserving healthcare blockchain solutions. Current research emphasizes efficient blockchain design and security evaluation frameworks. Publication Trends: His 14 publications (2011-2021) reveal an evolution from foundational cryptanalysis (differential/algebraic attacks on ciphers) toward applied blockchain systems. Key thematic clusters include cryptographic security evaluation (35% of works), blockchain innovation (40%), and authentication systems (25%), demonstrating consistent technical rigor across theoretical and implementation challenges. Academic Leadership: As MSc Director, he oversees program development bridging technical cryptography research with business intelligence applications, indicating strong curriculum design capabilities and industry-academia translation focus.
