جست‌وجوی استاد و پژوهشگر

Constandinos Mavromoustakisمشاهده پروفایل

استاد

• Internet of Things (IoT)
• Mobile and Wearable Computing
• Wireless Communications
• +۳ مورد دیگر

Constandinos Mavromoustakis is a Professor at the Department of Computer Science, University of Nicosia (School of Sciences and Engineering). He leads the Mobile Systems Lab (MOSys Lab) and holds leadership roles in IEEE, including Vice-Chair of the Cyprus Section and Chair of the Computer Society Chapter. He actively contributes to IEEE Communications Society committees and standardization groups like IEEE-SA SCC42 WG2040. Education includes: Dipl.Eng in Electronic and Computer Engineering from Technical University of Crete MSc in Telecommunications from University College London PhD from Aristotle University of Thessaloniki His research integrates Mobile Systems, IoT, and Wireless Communications, with emphasis on: 5G/6G network security using AI-driven strategies Resource optimization in cloud-edge ecosystems UAV-assisted networks for critical infrastructure Healthcare applications via IoMT and data analytics Recent publications (2024-2025) demonstrate strong focus on securing next-gen networks (O-RAN, 6G), optimizing edge computing for VR/IoT, and advancing smart healthcare/cities. Dominant themes include Deep Reinforcement Learning, quantum-inspired optimization, and latency minimization techniques. He participates in EU-funded initiatives including FP7, H2020, Eureka, and national projects. Industrial collaborations include consultancy for Intel Corporation. He directs the MOSys Lab, which researches mobile systems, IoT interoperability, and network security, with projects spanning UAV communications, medical IoT, and sustainable computing.

Seren BAŞARANمشاهده پروفایل

دانشیار

• Educational Technology
• Machine Learning
• Decision Analysis
• +۵ مورد دیگر

Assoc. Prof. Dr. Seren BAŞARAN is an academic faculty member at the Department of Computer Information Systems within the College of Engineering at Near East University . Her research focuses on educational technology, machine learning, decision analysis, and the integration of social media in higher education. She has contributed extensively to the development of e-learning systems, including the creation of the multilingual platform ‘Net-Class’. Specializations: Educational Technology, Fuzzy Logic Applications, Learning Analytics, Cloud Computing, Spectral Geometry, and Social Media in Pedagogy. Her recent work explores smart mobility data platforms, blended learning during the pandemic, and multi-criteria decision-making frameworks for evaluating digital learning tools. Despite her prolific publication record, no explicit information about scientific awards or advisees is available.

Ümit İLHANمشاهده پروفایل

استادیار

• Artificial Neural Networks
• Fuzzy Logic
• Machine Learning
• +۱ مورد دیگر

Assist. Prof. Dr. Ümit İLHAN is a full-time lecturer in the Department of Computer Engineering at the College of Engineering, Near East University. He joined the university in 2003 and was awarded the title of Assistant Professor in 2008. Previously, he served as a part-time lecturer at the university between 1990 and 2003 while working in the IT sector, including roles as IT Manager at Hürbank (1995–2003). He earned his Ph.D. from Near East University in 2007, focusing on Artificial Neural Networks and Fuzzy Logic. Education : Bachelor's in Computing from the Polytechnic of Central London (1981). His research interests center on Artificial Neural Networks and Fuzzy Logic , with publications in international conferences and journals. He has also contributed to applied computing projects, notably organizing general, local, and presidential elections in the Turkish Republic of Northern Cyprus as a software developer under a protocol between Near East University and the TRNC Supreme Election Committee. Additional roles include serving as Director of the Near East University Vocational School since 2008 and Vice Dean of the Engineering Faculty in 2008. He participates in competitions for vocational secondary schools as a jury member under the TRNC Ministry of Education. His career spans private teaching institutions, computer hardware sales, and software development before transitioning to academia.

Hamit ALTIPARMAKمشاهده پروفایل

مدرس

• Computer Engineering
• Software Development
• Networking
• +۲ مورد دیگر

Dr. Hamit ALTIPARMAK is a Lecturer in the Department of Computer Engineering at Near East University. He completed his B.Sc. and M.Sc. degrees in Computer Engineering at Near East University (2014) and is currently enrolled in a 4-year university degree program in business at Anadolu University. His research interests span core aspects of computer engineering including software development, networking, and data structures. Education B.Sc. in Computer Engineering, Near East University (2014) M.Sc. in Computer Engineering, Near East University (2014)

Oluwaseun Priscilla OLAWALEمشاهده پروفایل

مدرس

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Oluwaseun Priscilla Olawale is a Lecturer in Software Engineering at Near East University (Nicosia, Cyprus), where she is concurrently pursuing her master's degree in Software Engineering. She previously served as a teaching assistant at the same institution. Her academic background includes a Bachelor's degree in Computer Science from Bowen University, Nigeria, complemented by professional experience as an IT Specialist at the Standards Organisation of Nigeria and Software Developer at Royal Niger Company. Research Focus: Her work centers on developing reliable software solutions with emphasis on artificial intelligence applications. Primary domains include healthcare technology (medical imaging, remote healthcare, IoHT security), industrial systems (Industry 4.0 automation), cybersecurity (blockchain integration, anomaly detection), and educational technology (post-pandemic learning environments). She demonstrates consistent interest in interdisciplinary AI implementations bridging theoretical models and practical challenges. Publication Trends: Recent articles (2020-2025) reflect a progression from foundational surveys in data mining and blockchain verification toward applied AI solutions. Emerging themes include disaster prediction systems, audio-visual signal processing, and security-enhanced healthcare networks. Her technical approach frequently employs deep learning architectures (CNNs, VGG-16), blockchain frameworks, and signal processing techniques to address real-world problems across diverse sectors.

Çağrı ÖZKANمشاهده پروفایل

مدرس

• Arduino
• Big Data
• Metadata Analysis
• +۵ مورد دیگر

Çağrı ÖZKAN is a Lecturer in Information Systems Engineering at the College of Computer and Technology, Near East University. He holds an MSc in the same discipline and has served as Head of the Department of Computer Technologies and Programming in the Turkish Advanced Program since 2017. His research focuses on Arduino-based systems, Big Data analysis, metadata management, and Deep Learning applications. B.Sc., Information Systems Engineering, Near East University (2015) MSc., Information Systems Engineering, Near East University (2017) His recent publications explore interdisciplinary applications of Machine Learning in healthcare (diabetes, lung cancer, tumor classification) and environmental sustainability (carbon emission reduction, solar energy optimization). These works integrate IoT and AI for practical solutions in diverse domains. His teaching and research activities emphasize technology adoption patterns, as evidenced by studies on e-commerce in North Cyprus and hardware-software co-design for energy systems.

Peter Schwendnerمشاهده پروفایل

استاد

• Financial Risk Management
• Portfolio Management
• Machine Learning in Finance
• +۷ مورد دیگر

Peter Schwendner serves as Professor and Head of Institute of Wealth & Asset Management at ZHAW Zurich University of Applied Sciences, Department Banking, Finance, Insurance in Winterthur, Switzerland. With a PhD from Max Planck Institut für Strömungsforschung Göttingen and additional education in Foreign Affairs & Applied Diplomacy and University Didactics from ZHAW, he brings both academic rigor and practical industry experience to his role, having previously served as Head of Department at Sal. Oppenheim jr. & Cie and COO/Partner at Fortinbras Asset Management GmbH. Professor Schwendner's research focuses on the intersection of quantitative finance, machine learning, and sustainable investment. His work spans portfolio management techniques including risk parity approaches, correlation analysis in financial markets, ESG integration, and digital asset applications. Recent publications demonstrate particular emphasis on tokenization frameworks, AI-driven investment strategies, and biodiversity risk assessment in portfolio construction. His research often addresses European bond markets, correlation regimes, and the impact of ESG news on financial markets, combining theoretical models with empirical market data. With 76 publications and over 38,000 reads on ResearchGate, Professor Schwendner has established himself as a significant contributor to the field of quantitative finance. His recent work shows increasing focus on sustainable finance applications, with numerous publications on ESG integration, biodiversity risk assessment, and climate-related financial analysis. The trend in his publication record indicates growing attention to the practical implementation challenges of AI in investment processes and the evolving regulatory landscape for digital assets. As Head of Institute of Wealth & Asset Management, Professor Schwendner oversees research that bridges academic theory with practical financial applications. His work on correlation networks, adaptive risk parity approaches, and tokenization frameworks demonstrates his commitment to addressing current challenges in portfolio management and financial technology. His research group appears particularly focused on developing robust investment strategies that can navigate changing market conditions while incorporating sustainability considerations.

OlaOluwa Simon Yayaمشاهده پروفایل

دانشیار

• Time Series Econometrics
• Financial Econometrics
• Fractional Integration
• +۵ مورد دیگر

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 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.

Yanshuang Liمشاهده پروفایل

دانشیار

• Financial Econometrics
• Risk Spillovers
• Stock Markets
• +۵ مورد دیگر

Yanshuang Li is an Associate Professor in the Department of Finance at Dongbei University of Finance and Economics in Dalian, China. Her research examines risk transmission mechanisms in global financial systems using advanced econometric frameworks. Research Focus: Dr. Li's work spans: Financial econometrics and volatility modeling Cross-market risk spillovers during crises (pandemics, conflicts, climate policy shifts) Network analysis of interdependencies between commodities, equities, and emerging assets Behavioral aspects of market panic and investor sentiment Her publications demonstrate consistent focus on how systemic shocks propagate through stock, commodity, and renewable energy markets. Publication Trends: Recent articles (2023-2025) reveal: Growing emphasis on climate economics and AI-driven market analysis Methodological innovation in quantile-based connectedness frameworks Comparative studies of conventional and Islamic financial systems Empirical investigations into vaccination policies, sanctions, and green energy transitions

Fenghua Wenمشاهده پروفایل

استاد

• Financial Engineering
• Financial Risk Management
• Behavioral Finance
• +۵ مورد دیگر

Fenghua Wen is a Full Professor at Central South University, where he directs the Data Science and Economic Behavior Decision Research Center. His primary affiliation is with Central South University, where he leads interdisciplinary research combining finance, data science, and economic behavior analysis. Professor Wen's research spans multiple domains including: Financial engineering and risk management Climate economics and environmental policy impacts Behavioral finance and cultural influences on economic decisions Energy market dynamics and commodity price volatility Corporate governance and regulatory frameworks His work frequently employs advanced econometric and machine learning techniques to analyze market behaviors, particularly within Chinese financial systems. His recent publications demonstrate a strong focus on climate-related financial risks, including carbon market dynamics, corporate responses to environmental uncertainty, and AI applications in climate modeling. The research consistently examines policy implications, market efficiency, and risk mitigation strategies across financial and commodity markets. As Director of the Data Science and Economic Behavior Decision Research Center, he oversees investigations into economic decision-making processes, leveraging data science approaches to understand financial behaviors and systemic risks.

Mehmet Özsözمشاهده پروفایل

استاد

• Electrochemical Biosensors
• Analytical Chemistry
• Biomedical Engineering
• +۱ مورد دیگر

Prof. Dr. Mehmet Özsöz is a distinguished Professor in the Faculty of Biomedical Engineering at Near East University, with significant contributions to electrochemical biosensors and AI-integrated sensing technologies. His work bridges biomedical engineering and artificial intelligence through the university's AI Research Center. His academic journey includes: Bachelor of Science in Chemical Engineering from Middle East Technical University PhD in Analytical Chemistry from Ege University's Faculty of Pharmacy Two years of postdoctoral research in the United States on electrochemical biosensors Prof. Özsöz's research focuses on electrochemical biosensor development , advanced analytical chemistry techniques , and artificial intelligence applications in biomedical sensing . His interdisciplinary approach has yielded publications in premier journals including ACS Analytical Chemistry, Chemical Communications, and Biosensors & Bioelectronics, demonstrating significant impact in both engineering and medical diagnostics fields. His distinguished achievements include: 2008 TUBITAK Science Award for groundbreaking work on Electrochemical Biosensors Recognition as #45 in Sanko Holding's '100 Turks Who Guide Science' (2017) With 150 scientific publications and an h-index of 46, Prof. Özsöz maintains an exceptional research trajectory. His 50+ international invited presentations confirm his global standing, while his leadership in the university's AI Research Center demonstrates commitment to cutting-edge interdisciplinary collaboration. Though specific grant details aren't provided, his publication volume and high-impact journal placements indicate sustained research funding and academic productivity. Prof. Özsöz actively contributes to Near East University's Artificial Intelligence Research Center, fostering synergies between biomedical engineering and machine learning for next-generation diagnostic technologies.

• Supply Chain Management
• Operations Management
• Data Analytics
• +۱ مورد دیگر

Dr. Adil Akaaboune is a full-time Assistant Professor in the School of Business Administration. He holds a Ph.D. in Engineering Sciences from the United States, specializing in Industrial Engineering and Logistics. His professional background includes significant industry experience as an engineer and consultant at corporations such as INTEL and DELOITTE. His research applies data analytics and machine learning to advance Supply Chain Management and Operations Management , bridging theoretical frameworks with practical industrial challenges.

Nasser Assemمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Big Data
• +۳ مورد دیگر

Nasser Assem serves as Associate Professor of Computer Science and Academic Coordinator for undergraduate and graduate Computing programs at Al Akhawayn University's School of Science and Engineering. A full-time faculty member, he maintains regular office hours across four weekdays in Building 7, Office 9. His educational foundation includes: PhD in Computer Science, Michigan State University (2002) MS in Computer Science, Michigan State University (1995) Bachelor's in Electrical/Computer Engineering, Mohammadia School of Engineering, Rabat (1988) Research expertise spans: Core methodologies: Machine Learning and Artificial Intelligence Data systems: Big Data analytics, Database management, and Business Intelligence Infrastructure: Cloud Computing platforms Industry certifications from IBM validate his technical proficiency in these domains, while national R&D project involvement demonstrates real-world application. His academic journey includes a visiting position at Michigan State University (2002-2003) following graduate studies, preceded by five years as Computer Engineer/IT Manager at Morocco's Ministry of Public Works. Professional recognition: Current Chair of IEEE Morocco IBM certifications in AI, Big Data, and Cloud Computing As Academic Coordinator, he oversees program development while contributing to university governance through committee leadership. His conference organization roles and IEEE chairmanship indicate strong national and international academic engagement. Though no dedicated research lab is mentioned, his focus areas suggest collaboration with data science teams addressing Morocco's technological challenges.

• collaborative self-protecting software
• unsupervised machine learning
• application-level intrusion detection

Omar Iraqi Houssaini serves as a full-time Lecturer in the School of Science and Engineering at Al Akhawayn University in Ifrane, where he has taught computer science and cybersecurity courses at undergraduate and graduate levels since 2003. His institutional roles include prior service as IT Manager (2005-2009) and IT Director (2009-2012) at the same university. His academic credentials include: Ingénieur d'Etat from EMI (Ecole Mohammadia d'Ingénieurs) in Rabat MSc in Computer Networks from Al Akhawayn University (2003) Ph.D. in Computer Science from Mohammed V University in Rabat (defended 2022) Dr. Houssaini's research centers on collaborative self-protecting software , unsupervised machine learning , and application-level intrusion detection . His work develops autonomous cybersecurity systems that detect and neutralize threats without human intervention, merging theoretical computer science with practical security implementations. Professional certifications form a critical component of his expertise: CISSP (Certified Information Systems Security Professional) CISA (Certified Information Systems Auditor) ISO 27000 standards certification These industry credentials complement his academic role, providing students with real-world security management perspectives alongside theoretical instruction.