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Husnu Yenigun is a Professor at Sabanci University's Computer Science and Engineering Program , Faculty of Engineering and Natural Sciences (Istanbul, Turkey). He earned his BSc, MSc, and PhD in Electrical and Electronics Engineering from Middle East Technical University (Ankara) in 1992, 1995, and 2000 respectively. His professional career includes roles at TUBITAK (1992-1997), Bell Laboratories (1997-1998), and as a consultant at Bell Labs (1999-2000). Research interests: Dr. Yenigun specializes in automata and concurrency theory, formal methods, software quality assurance, model checking, and complexity relief techniques for software verification. His work bridges theoretical automata analysis with practical testing frameworks. Key publication trends: His recent work spans automata synchronization (2018-2021), matrix optimization (2017-2018), and adaptive testing sequences (2016-2018), with applications in Wireless positioning systems Finite state machine verification Parallel computing Formal method implementations Professional activities: He serves on technical program committees for major conferences like MODELSWARD, QRS, and ICTSS (2016-2025). He chaired the programming committee for ICTSS 2013 and 2017, and co-chaired UYMS 2018. He also acted as guest editor for the International Journal on Software Tools for Technology Transfer (2016). Contact: yenigun@sabanciuniv.edu | Office: FENS 2054, Sabanci University

• Automata Theory
• Concurrency Theory
• Formal Methods
• +5 more

Prof. Dr. Sona Mardikyan is a faculty member at Bogazici University, specializing in quantitative methods and information systems. Her educational background includes a B.S. in Control and Computer Engineering from Istanbul Technical University, an M.A. in Industrial Engineering from Bogazici University, and a Ph.D. in Business Administration (Quantitative Techniques) from Istanbul University. She teaches courses such as Statistics, Data Mining, Multivariate Statistical Methods, and Information Systems Technologies. Her research focuses on Information Systems , Multivariate Statistics , Data Mining , and e-Learning . She investigates technology adoption patterns, social media analytics, educational technology impacts, and e-commerce optimization, often using advanced statistical modeling and AI techniques. Her publications emphasize emerging technological trends, including AI-driven customer analytics, social media metrics, IoT scientometrics, and digital transformation in education and business. A consistent focus on empirical validation and real-world applications characterizes her work. Awards: Best Paper Award at the 5th International Management Information Systems Conference (2018) for research on call center efficiency using text mining. She actively mentors academic projects and contributes to international conferences, though specific student advisees and grants are not detailed in the source material.

• Information Systems
• Multivariate Statistics
• Data Mining
• +1 more

N. Ziya Perdahçı is an Associate Professor at Bogazici University, specializing in Management Information Systems . His research focuses on network science applied to social, educational, and business contexts, including stochastic block models, customer segmentation, and digital platform analysis. He teaches courses in programming, databases, and business application development. Education: Undergraduate: Bogazici University, Physics M.A.: Bogazici University, Physics Ph.D.: Bogazici University, Physics Research Interests: Stochastic Block Models Statistical Social Network Analysis Customer/Product Segmentation Technology Adoption Users’ Interconnectedness Analytics Social Network Correlations Patents: Electricity generation device (TR 2007 07104B, 2007) Ceramic sliced helical heater (24466, 1990) His recent work explores digitalization in art (NFTs, Metaverse), technology acceptance models for website analysis, and co-purchase behavior in e-commerce. He has published extensively on network-based theories in education, healthcare, and cloud computing environments. He collaborates frequently with Mehmet Nafiz Aydin and Kenan Kafkas on interdisciplinary projects combining physics principles with information systems research. His book chapters cover metadata action networks and big data analytics frameworks.

• Network Science
• Social Network Analysis
• Data Analytics
• +3 more

Birgül Kutlu Bayraktar is a Professor at Boğaziçi University, Turkey, with a distinguished career spanning over two decades in information systems and educational technologies. Her work bridges theoretical computer science with practical applications in learning environments and corporate training. Her academic foundation includes: High School: BAL Undergraduate: Boğaziçi University, Electrical Engineering Masters: Michigan Tech University, Electrical Engineering Ph.D.: Ege University, Computer Engineering Professor Kutlu Bayraktar's research centers on Information Systems , Remote Education , Artificial Neural Networks , and Artificial Intelligence , with significant contributions to Recommender Systems , Learning Management Systems , and Serious Games . Her work explores how technology enhances educational outcomes, particularly through mobile and virtual environments, while addressing corporate e-learning adoption and location-based social applications. She emphasizes user experience and behavioral impacts in digital learning contexts. Analysis of her 2013-2020 publications reveals a strong trajectory in AI-driven educational tools, including mobile serious games for programming education and hybrid recommender systems for location-based services. Her research consistently connects theoretical models with empirical studies in Turkish and international contexts, demonstrating expertise in both quantitative analysis and human-centered design. Scientific Awards: No awards were documented in the source material. Regarding academic mentorship, the provided information does not specify supervisees or grant funding, though her extensive publication record suggests significant research leadership. No dedicated laboratories or formal research teams are mentioned, though her frequent collaborations with researchers like A. Bozanta and H. Kimiloglu indicate active interdisciplinary networks.

• Information Systems
• Remote Education
• Artificial Neural Networks
• +4 more

Ahmet Onur Durahim is a Lecturer at Boğaziçi University , specializing in Artificial Intelligence, Big Data Analytics, and Cybersecurity. With a PhD in Computer Science and Engineering from Sabancı University, his research focuses on social media analysis, cryptographic protocols, and network security. Education: Sakarya Anadolu Lisesi (High School) Boğaziçi University: B.S. in Industrial Engineering and Construction Engineering (Double Major) Boğaziçi University: M.S. in Civil Engineering Sabancı University: PhD in Computer Science and Engineering Durahim's research spans AI applications in social media, big data processing, and security protocols for wireless networks. His work includes sentiment analysis on Twitter, spam detection frameworks, and cryptographic authentication systems. Recent publications highlight his contributions to cryptocurrency interest identification, music emotion classification, and spam review detection. His methodological focus includes semi-supervised learning and imbalanced data handling.

• Artificial Intelligence
• Big Data Analytics
• Social Network Analysis
• +4 more

Zuhal Tanrıkulu is a Professor in the field of Management Information Systems, with a multidisciplinary background in Electronics and Communication Engineering, Control and Computer Engineering, and Business Administration. She has taught courses spanning enterprise information systems, global IS success metrics, soft computing applications, and graduate seminars. Research Focus: Her work centers on information systems development, systems success/failure analysis, e-learning technologies, and health information systems. Recent publications emphasize password security algorithms, mobile learning sustainability, and data mining applications. Publication Trends: Over the past decade, her research spans cybersecurity, digital transformation, and educational technology. Key subfields include network security protocols, business model innovation, and intelligent system integration in service processes.

• Information Systems Development
• Information Systems Management
• Systems Success and Failure
• +3 more

Semiha Tedik Başaran is an Assistant Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University's Faculty of Electrical and Electronics Engineering. She received her PhD in Telecommunications Engineering from Istanbul Technical University in 2019 and has been working at the university since 2011, first as a Research Assistant and then as an Assistant Professor starting in 2020. Her educational background includes: PhD in Telecommunications Engineering from Istanbul Technical University (2013-2019) MSc in Telecommunications Engineering with Thesis from Istanbul Technical University (2011-2013) Bachelor's Degree in Electronics and Communication Engineering (Double Major) from Istanbul Technical University (2006-2011) Dr. Başaran's research focuses on wireless communications, network coding, and next-generation wireless networks. Her work spans theoretical analysis and practical implementation of communication systems, with particular emphasis on network coded cooperation, physical layer security, and wireless network reliability. She has made significant contributions to understanding the performance of network coded systems in various wireless environments, including satellite communications and 5G/6G networks. Her recent publications demonstrate a growing interest in integrating artificial intelligence with wireless communications, particularly for IoT applications and edge computing, while also advancing research in THz communication systems and their challenges in adverse weather conditions. Her scientific achievements have been recognized with several prestigious awards: Doctoral Thesis Award from Istanbul Technical University (2020) IEEE Türkiye Doctoral Thesis Award (2020) Best Poster Award at IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE-2016) (2016) Dr. Başaran serves as Principal Investigator for multiple research projects including 'Designing 5G and Beyond Cellular Private Networks Secure Against DDoS Attacks,' 'Performance Analysis of THz Communication Systems,' 'Coverage Analysis of LEO Satellite Systems,' and 'Development of Multiple Access Techniques Providing Low Latency Performance for Next Generation Communication Systems.' Her h-index of 8 (based on Scopus) reflects her impactful contributions to the field of wireless communications, with 36 research outputs spanning from 2013 to 2024. She maintains an active research lab focused on wireless communications and network coding, where her team works on both theoretical analysis and practical implementation of next-generation communication systems using software-defined radio platforms, with strong international collaborations extending across multiple countries as indicated by her research footprint.

• Wireless communications
• Network coding
• 5G and beyond networks
• +7 more

Professor AYDIN OZBEK serves as a full Professor in the Department of Basic Medical Sciences at Istinye University School of Medicine. With a career spanning over three decades since his medical education began in 1979, he maintains active research and teaching roles in anatomy and sports medicine. His institutional affiliation is exclusively with Istinye University as evidenced by his faculty listing and university email domain. Research interests center on clinical anatomy (particularly anatomical variations), sports medicine (focusing on physiological responses in footballers, basketball players, and tennis athletes), and neurophysiology (nerve conduction studies in sports contexts). His work uniquely bridges fundamental anatomical research with applied sports science, examining how repetitive motion affects neuromuscular function and biochemical markers in elite athletes. Recent publication analysis (2009-2017) reveals a strategic shift from pure anatomical variation studies toward sports physiology applications. Approximately 65% of recent work examines athlete biomarkers (ischemia-modified albumin, neurotrophins), nerve conduction changes, and biomechanics. Methodologically, research evolved from case reports to controlled cohort studies, frequently comparing elite athletes against control groups. Key themes include soccer heading neurotoxicity, sport-specific nerve stress, and metabolic responses to training. TUBITAK Incentive Award (2004) - Turkey's highest early-career scientific honor Author of standard Turkish medical textbooks including 'Medical Terminology and Etymology' and 'ANATOMY TEXTBOOK' Extensive publication record with 50+ articles on anatomical variations and sports physiology Professor Ozbek maintains strong collaborative networks, frequently publishing with colleagues Tuncay Colak and Belgin Bamac across multiple departments. His research demonstrates consistent funding support through institutional resources and national research programs, particularly evident in the longitudinal sports medicine studies requiring specialized equipment for biochemical and electrophysiological measurements. While no formal lab is named, his work leverages university facilities for anatomy instruction and sports physiology testing.

• Anatomy
• Sports Medicine
• Neurophysiology
• +4 more

Associate Professor Bedri Kurtulus is affiliated with Muğla Sıtkı Koçman University , where he serves in the Faculty of Engineering under the Department of Geological Engineering . His academic journey includes a Bachelor's from Hacettepe University, a Master's from Université de Poitiers, and a Ph.D. in Hydrogeological Engineering from Hacettepe University. Education: B.Sc. Geological Engineering, Hacettepe University M.Sc. Hydrogeology, Université de Poitiers Ph.D. Hydrogeological Engineering, Hacettepe University Research Interests: His work focuses on karstic aquifers , groundwater modeling , remote sensing applications in hydrology, and environmental pollution assessment . He employs computational intelligence methods like ANFIS and neural networks to analyze hydrological systems and has pioneered studies on microplastic transport in porous media. Recent Publications highlight his expertise in GIS-based interpolation techniques , thermal stratification of lakes , and karst spring characterization . He has mentored multiple students in projects ranging from groundwater resilience to climate change to UAV-based hydrological monitoring .

• Hydrogeology
• Karstic Aquifers
• Remote Sensing
• +5 more

Ceyhun Özçelik is an Associate Professor in the Department of Civil Engineering at Muğla Sıtkı Koçman University, specializing in Water Resources Engineering with a focus on flood modeling, remote sensing, and Geographic Information Systems (GIS). His academic journey includes a Bachelor's and Master's degrees in Civil Engineering from Pamukkale University (1999, 2002), a second Master's in Geographical Information Systems from Dokuz Eylül University (2006), and a Doctorate in Civil Engineering from Dokuz Eylül University (2007). Özçelik's research interests span water resources engineering, flood modeling, remote sensing applications, hydrological analysis, and drought assessment. His work demonstrates a strong integration of GIS technologies with traditional hydrological methods to address complex water management challenges. He has developed spatiotemporal models for monthly flows and runoff by coupling GIS and remote sensing techniques, contributing significantly to the field of water resources management. His publication record shows consistent scholarly output with recent articles focusing on watershed flood risk indices, drought assessment using satellite observations, and analysis of flood events in Turkey. His research has practical applications in disaster management, particularly in flood risk assessment and response systems like the 'Akıllı CanMELEK' mobile tracking and communication system he developed. Uygulama Yarışması Birincisi, 18. Esri Kullanıcıları Konferansı (2013) Doktora Tez Ödülü (2008) Postdoctoral Fellowship for Foreign Researchers (2008) Turkish-Indian Cultural Exchange Program (1st among 12 candidates) (2007) Özçelik has supervised numerous graduate students working on topics including flood simulation, drought analysis, water distribution systems, and GIS applications in water resources. He has served as principal investigator for multiple research projects funded by various institutions including TÜBİTAK and the Development Agency, with recent work focusing on flood risk analysis in Bodrum, Şanlıurfa flood disaster comparison, and hydrological analysis of Gökçeler Stream. He actively contributes to the academic community through editorial work for journals including Teknik Dergi, Journal of Hydrology, and Water Resources Management, and has participated in numerous national and international conferences presenting his research on water resources and flood management.

• Water Resources Engineering
• Flood Modeling
• Remote Sensing
• +5 more

Aydın GÜLLÜ is an Assistant Professor at Trakya University's Vocational School, where he has served as Head of the Electronics and Automation Department since 2013. His academic career spans over 14 years, including roles as Instructor (2010) and Administrative Director of Kesan Vocational School since 2024. Educational Background: PhD in Mechanical Engineering (Trakya University, 2017) MSc in Mechatronics (Marmara University, 2010) BSc in Mechatronics Education (Marmara University, 2009) Associate Degree in Electronics (2004) His research focuses on robotics, artificial intelligence, and automation. Key areas include mobile robot navigation , image processing for engineering , and renewable energy systems . He has developed training equipment for servo motors, SCADA systems, and solar-powered applications. Research Trends: Recent work involves UAV development (2023), automotive collision simulation (2023), and robot exploration algorithms (2021). Earlier studies (2016–2020) concentrated on image processing , solar energy , and industrial automation . Scientific Achievements: Best Paper Award at UTES 2016 Top Student in Mechatronics Education (Marmara University, 2009) He has secured grants for laboratory modernization projects and developed robot competition frameworks at Trakya University. His collaborations span Bulgaria, Turkey, Germany, and Czech Republic, with active participation in international conferences like UNITECH and INES.

• Robotics
• Artificial Intelligence
• Control Systems
• +4 more

Önder AYER is an Associate Professor at Trakya University's Faculty of Engineering, Department of Mechanical Engineering, specializing in Machine Theory and Dynamics. He currently serves as Deputy Head of Department (since February 28, 2025), Faculty Board Member (since March 2024 and June 2024), and Erasmus Coordinator (since November 2012). His educational background includes a Bachelor's (2003), Master's (2006), and PhD (2012), all in Mechanical Engineering from Trakya University. His academic progression shows steady advancement from Research Assistant (2004) to Associate Professor (2021). Dr. AYER's research focuses on mechanical engineering with emphasis on extrusion processes, magnesium alloys, gear forming, and finite element analysis. His work bridges theoretical modeling with practical manufacturing applications, particularly examining material behavior during forming processes. He has extensively studied AZ31 magnesium alloys, investigating their machinability, microstructure, and forming characteristics under various extrusion parameters. His publication record shows consistent output with a focus on manufacturing processes, particularly extrusion technologies. The research demonstrates progression from fundamental material studies to advanced applications involving artificial neural networks for process prediction. Recent publications (2020-2022) continue to explore material behavior under manufacturing conditions, with applications in aluminum and magnesium processing. Dr. AYER teaches courses including Aluminum Alloys Forming, Aluminum Extrusion Technology, Non-Traditional Production Methods, and Mechanism Technique. His teaching directly complements his research interests, creating a cohesive academic profile focused on advanced manufacturing technologies. He has served as Erasmus Coordinator since 2012, indicating strong international engagement. His administrative roles, including Deputy Head of Department since 2025, demonstrate leadership within the department. His research project on applying artificial neural networks and finite element methods to extrusion process optimization (2016) represents a significant contribution to the field.

• Mechanical Engineering
• Materials Science
• Extrusion Processes
• +4 more

Meltem KARAATLI is a Professor at the Faculty of Economics and Administrative Sciences, Süleyman Demirel University, with expertise in artificial neural networks and operations research. She holds a PhD in Business Administration from Süleyman Demirel University (2010), following an MSc (2005) and BSc (1999) in Industrial Engineering and Business Administration, respectively. Her research focuses on applying data mining and machine learning techniques to financial and economic problems, including stock market analysis, forecasting, and decision-making. Recent work explores cryptocurrency portfolio management (2024), Baltic Dry Index prediction (2023), and pandemic-era market clustering (2022-2021). She frequently employs NARX neural networks, LSTM/GRU models, and association rule mining. Publications span internationally refereed journals and national journals, with 15 recent articles (2021-2024) addressing topics like container port logistics (2022), football match modeling (2021), and hospital performance evaluation (2021). She co-authored the book "Social Aspects of COVID-19" (2021, IKSAD) and contributed to "SPSS Applied Multivariate Statistical Techniques" (2005, Asil Publications).

• artificial neural networks
• operations research

Ayşe DURGUN KAYGISIZ is a Professor at the Department of Economics, Faculty of Economics and Administrative Sciences, Süleyman Demirel University. Her research focuses on Tourism, Regional Development, Financial Crises, and Macroeconomics , with a strong emphasis on empirical analysis of economic policy. Education : Associate Degree in Justice (Anadolu University, 2015), Licence in Economics (Süleyman Demirel University, 2003), MA in Economics (Süleyman Demirel University, 2006), PhD in Economics (Süleyman Demirel University, 2010). Her work spans topics like energy economics, inflation dynamics, digital transformation in public finance, and demographic impacts on growth . Recent publications analyze AI applications, tourism's regional role, and macroeconomic effects of global crises. She has presented at international conferences (e.g., BALKAN 12th International Conference on Social Sciences) and contributed to books on inflation and economic policy. Her methodological expertise includes panel data analysis, causality models, and SWOT-AHP frameworks.

• Tourism
• Regional Development
• Financial Crises
• +3 more

Shahaboddin Daneshvar is a full-time Assistant Professor in the Department of Computer Engineering at the College of Engineering, Hasan Kalyoncu University. His academic journey includes a BSc (2011), MSc (2014), and PhD (2021) in Computer Engineering from Islamic Azad University, Çukurova University, and Çukurova University respectively. Education: BSc, MSc, PhD in Computer Engineering Current Affiliation: Hasan Kalyoncu University, College of Engineering Daneshvar's research focuses on applying machine learning and data analysis to sports engineering , particularly cross-country skiing performance prediction. His work integrates techniques like Relief-F feature selection and support vector machines with biomechanical data to model athletic outcomes. Recent publications demonstrate trends in using computational models for sports analytics, including predictive modeling of racing times and upper body power metrics. These studies leverage data mining and neural networks to optimize performance predictions without requiring direct exercise testing.

• Machine Learning
• Sports Engineering
• Computer Science
• +3 more