جست‌وجوی استاد و پژوهشگر

• Information Retrieval
• Natural Language Processing
• Turkish Language Processing
• +۴ مورد دیگر

Bekir Taner Dincer is a Professor at Muğla Sıtkı Koçman University, Faculty of Engineering, Department of Computer Engineering. He has been actively teaching courses including Web Development and Programming, Artificial Intelligence, Data Mining, Natural Language Processing, and Senior Design Projects for multiple academic years including the upcoming 2025-2026 term. Dr. Dincer earned his Bachelor's degree in Statistics from Middle East Technical University (1988-1993), followed by a Master's degree in Statistics and Computer Science from Muğla Sıtkı Koçman University (1996-1998), and completed his Doctorate in Computer Science from Ege University's International Computer Institute (1998-2004). His research focuses on Information Retrieval, Natural Language Processing (particularly for Turkish language), and related computational linguistics areas. His work addresses challenges in Turkish language processing including morphological analysis, constituent chunking, information retrieval systems, and term weighting methods. He has made significant contributions to adapting information retrieval techniques for agglutinative languages like Turkish, which presents unique challenges compared to Indo-European languages. His publication record shows a consistent research trajectory with recent work (2013-2018) focusing on risk-sensitive evaluation methods, learning to rank, entity recognition in big data, and specialized approaches for Turkish language processing. His research often bridges theoretical information retrieval concepts with practical applications for Turkish text processing. Dr. Dincer has served as editor for prestigious publications including the International ACM SIGIR Conference proceedings and ACM Transactions on Information Systems journal, demonstrating recognition of his expertise by the international research community. He has supervised numerous graduate students, guiding PhD and Master's theses on topics including unsupervised syntactic disambiguation for Turkish, statistical analysis of word roots and affixes, and information retrieval system design. His research has been supported by TÜBİTAK projects including the Design of a Statistics-Driven Selective Information Retrieval System (2015-2018) and the Design of a Statistical Information Access System (2011-2014).

Selçuk Karabatıمشاهده پروفایل

استاد

• Retail Operations Management
• Sustainable Operations Management
• Supply Chain Management
• +۳ مورد دیگر

Selçuk Karabatı is a Professor of Operations Management at the College of Administrative Sciences and Economics, Koç University (Turkey). His research spans retail operations, sustainable supply chains, and production systems optimization. He holds a PhD from the University of Texas at Austin and has previously taught graduate courses in Service Operations Management , Operations Strategy , and Sustainable Operations Management at Koç University. Education : PhD (University of Texas at Austin), MS (University of Southern California), BS (Boğaziçi University) Editorial Roles : Senior/Associate Editor at Production and Operations Management and IIE Transactions His research focuses on Supply Chain Management , Retail Operations , and Sustainable Operations , with applications in inventory control, pricing strategies, and production planning. Recent and historical publications reveal expertise in optimization frameworks , dynamic pricing , portfolio rebalancing , and retail analytics . While no explicit scientific awards are listed in the provided text, his work has consistently addressed challenges in inventory substitution, auction mechanisms, and logistics coordination.

Eray Yücelمشاهده پروفایل

مدرس

• Applied Econometrics
• Monetary Economics
• Macroeconomics
• +۲ مورد دیگر

Eray Yücel is a Lecturer in the Department of Economics at Bilkent University since 2017. He holds a PhD in Economics (2005) and MA in Economics (2000) from Bilkent University, with a B.Sc in Industrial Engineering (1998). His academic career includes roles as Associate Professor at Kadir Has University (2014-2016), part-time lecturing at multiple institutions, and 10 years as an Economist at the Central Bank of the Republic of Turkey (2003-2013) where he served as Managing Editor of the Central Bank Review (2005-2013).

• Economics
• Econometrics
• Financial Markets
• +۵ مورد دیگر

Bülent Güloğlu is a Professor at the Department of Economics, Istanbul Technical University, specializing in econometric modeling, financial markets, and energy economics. His research spans nonlinear tail dependencies, structural change analysis, and sustainable development. Research interests include: Quantile regression applications in banking risk analysis Nonlinear dynamics in energy-agricultural commodity markets ESG metrics and corporate risk dependency Energy productivity in Türkiye's economic transformation Financial contagion and market interconnectivity Recent publications focus on sustainable photovoltaic policies, tail dependence analysis, and AI-enhanced decision models. His work has received Scopus citations and a Best Paper award in 2017. Scientific awards: Best Paper Prize, Istanbul Technical University (2017) Current projects include ESG risk analysis, energy efficiency impacts on carbon emissions, and nonlinear energy market modeling.

Mohammad Qamarul Islamمشاهده پروفایل

استاد

• Statistical Inference
• Robust Statistical Methods
• Nonparametric Methods
• +۴ مورد دیگر

Prof. Mohammad Qamarul Islam is a Professor in the Statistics Department at Middle East Technical University (METU), Turkey, a position held since 2016. Previously, he served as Professor (2010-2016), Associate Professor (2005-2010), and Assistant Professor (1999-2005) in the Economics Department at Cankaya University. His academic career spans over four decades with prior appointments at METU (1983-1999) and Pakistani institutions including Gomal University and Karachi University. Education: Ph.D. in Statistics (1989), Middle East Technical University, Turkey M.Sc. in Statistics (1972), University of Karachi, Pakistan Research Focus: Prof. Islam specializes in advanced statistical methodologies with emphasis on Statistical Inference and Robust Methods . His work bridges theoretical statistics and practical applications through Nonparametric Techniques , Multivariate Analysis , and Econometric Modeling . Current investigations focus on regression under non-standard error distributions and experimental design optimization, contributing significantly to statistical theory validation in real-world scenarios. Publication Trends: His 2012-2016 publications reveal concentrated expertise in multivariate regression under non-ideal conditions (non-normal/elliptical errors), demonstrating methodological innovations for robust parameter estimation. Recent work extends to model uncertainty quantification in time series, reflecting his evolving focus on practical statistical challenges in economic and scientific data analysis. Academic Service: Information regarding student advising, research grants, laboratory affiliations, or scientific awards is not documented in the provided materials.

• Statistics
• Econometrics
• Panel Data Analysis
• +۵ مورد دیگر

Assoc. Prof. Elif Tuna serves in the Department of Statistics at Yildiz Technical University's Faculty of Arts & Science, where she advanced from Research Assistant (2002) to Assistant Professor (2012) before promotion to Associate Professor. Her doctoral training in Econometrics at Marmara University established her interdisciplinary approach bridging statistical theory and socioeconomic applications. Her educational qualifications include: Doctorate in Econometrics, Marmara University (2005-2010) Postgraduate in Statistics, Yildiz Technical University (2002-2005) Undergraduate in Econometrics, Istanbul University (1997-2001) Tuna's research centers on entropy-based statistical methodologies, panel data modeling, and nonlinear econometric analysis. She pioneers applications in environmental economics (Environmental Kuznets Curve validation), happiness economics during crises, and market concentration metrics. Her work consistently integrates information theory with real-world socioeconomic phenomena, particularly migration patterns and pandemic impacts. Recent publications (2021-2024) reveal intensified focus on dynamic modeling of pandemic effects using Markov switching frameworks, while maintaining her foundational work on entropy applications. She demonstrates methodological versatility across time series, panel data, and categorical analysis, with geographic emphasis on Turkish socioeconomic contexts. Scientific Awards: No awards documented in source materials She has supervised 2 graduate theses and contributed to two major funded projects: a 2014-2016 basin-level water resource study and a 2005-2007 nationwide evaluation of Turkish statistics education. Her collaborative work often involves cross-disciplinary teams from economics and environmental science departments. No dedicated laboratory facilities or permanent research teams are specified, though her project involvement suggests participation in university-wide research consortia.

Gulser Köksalمشاهده پروفایل

استاد

• Quality Engineering
• Statistical Process Control
• Robust Design
• +۶ مورد دیگر

Professor Gulser Köksal is a distinguished academic in the Department of Industrial Engineering at TED University. She previously served as Professor at Middle East Technical University (METU) from 1993 to present, holding significant administrative roles including Vice Rector (2017-2019) and Advisor to the Rector (2016-2017). Her academic journey includes positions as Associate Professor (1999-2006) and Assistant Professor (1993-1999) at METU, and Assistant at North Carolina State University (1988-1993). Her educational background includes a PhD in Industrial and Systems Engineering from North Carolina State University (1987-1992), an MS in Industrial Engineering from Middle East Technical University (1985-1987), and a BS in Industrial Engineering from the same institution (1980-1985). She is proficient in English at an advanced level (C1). Professor Köksal's research focuses on quality engineering, statistical process control, robust design methodologies, and data mining applications for quality improvement. Her work bridges theoretical statistical methods with practical industrial applications, particularly in multi-response optimization, desirability functions, and quality function deployment. She has made significant contributions to understanding inspection errors, rework processes, and their economic impacts on quality characteristics. Her publication portfolio demonstrates a consistent trajectory from foundational work in statistical process control to more recent applications of machine learning and neural networks in quality engineering. The research shows strong emphasis on practical industrial applications while maintaining theoretical rigor, particularly in handling categorical responses, uncertainty modeling, and multi-criteria decision making in product design. Professor Köksal has successfully supervised 64 theses across doctoral and master's levels, demonstrating her commitment to academic mentorship. Her research has been supported by numerous projects from TÜBİTAK, Erasmus, and Teknopark, totaling 21 projects. These projects span quality engineering, data mining applications, product design optimization, and strategic university governance. She has contributed to the academic community through extensive service, including participation in international conferences, workshops on quality engineering and higher education leadership, and collaborative research projects with institutions across Europe and China. Her work on university governance, particularly through the LEAD project, demonstrates her commitment to advancing academic leadership practices.

• Data Science & Analytics
• Data Mining
• Computational Statistics
• +۵ مورد دیگر

Inci Batmaz is a Professor of Statistics at the Middle East Technical University (METU) in Ankara, Turkey. She holds a dual Ph.D. in Computer Engineering (Ege University, Turkey) and a Dissertation from Carnegie-Mellon University (USA) as a Fulbright Scholar. Her academic career includes roles such as Chair of the Department of Statistics (2012–2015), Graduate Program Coordinator, and membership in various institutional boards. She has been affiliated with the Financial Mathematics Program at METU's Institute of Applied Mathematics since 2003. Her research focuses on Data Science & Analytics, Data Mining, Computational Statistics, Machine Learning, and Environmental Statistics. She has published extensively in top journals and edited volumes, including Recent Advances in Statistics (2007) and contributed to climate change studies, financial modeling, and simulation metamodeling. Dr. Batmaz has been recognized with multiple awards, including METU Publication Awards (2007–2016), TÜBİTAK Fellowships, and the Netherlands National Research Foundation Grant (2002). Her work bridges statistical methodology with real-world applications in climate science, finance, and industrial quality improvement.

Guvenc Arslanمشاهده پروفایل

استاد

• Statistics
• Machine Learning
• Data Mining
• +۴ مورد دیگر

Guvenc Arslan serves as a Professor in the Department of Statistics within the Faculty of Engineering and Natural Sciences, focusing on advanced statistical methodologies and machine learning applications. His work bridges theoretical statistics with real-world problem solving across diverse domains. His core research interests include: Machine Learning and Classification Algorithms Statistical Clustering Methods Applied Statistics in Healthcare and Earth Sciences Data Mining and Pattern Recognition Fuzzy Logic and Bayesian Methods Parameter Estimation and Distribution Theory Analysis of his 15 most recent publications (2024-2015) reveals consistent innovation in classification techniques, particularly for medical diagnostics (e.g., COVID-19, cryotherapy) and environmental monitoring (e.g., earthquake engineering, satellite data analysis). His methodology frequently integrates support vector machines, k-means clustering, and fuzzy Bayesian approaches to address complex data challenges. Dr. Arslan's scholarly contributions extend to software development, including a JAVA implementation for multivariate statistical testing, demonstrating his commitment to practical tool creation alongside theoretical advancement. His research maintains strong connections to both medical applications and geospatial engineering problems.

• Mathematics Education
• Statistics
• Applied Statistics
• +۴ مورد دیگر

Associate Professor RECEP BİNDAK is a faculty member at Gaziantep University's Faculty of Education, Department of Mathematics and Science Education. With a Doctorate in Mathematics from Dicle University (2004), he has built an extensive academic career spanning over two decades, including positions at Mardin Artuklu University and Gaziantep University's Technical Sciences Vocational School. His educational background includes a Doctorate (2000-2004) from Dicle University's Institute of Sciences in Mathematics, a Master's degree (1994-1997) from Yuzuncuyil University's Institute of Sciences in Mathematics, and a Bachelor's degree (1987-1991) in Mathematics Teaching from Dicle University's Faculty of Education. BINDAK's research focuses on mathematics education, statistics, and educational psychology, with particular emphasis on mathematical self-efficacy, problem-solving attitudes, measurement techniques, and quantitative research methods. His work bridges theoretical statistical concepts with practical educational applications, making significant contributions to both fields. He has published extensively on topics ranging from mathematical justification skills in middle school students to psychometric properties of Likert scales and teacher burnout predictors. His recent publications (2018-2024) reveal a strong trend toward interdisciplinary research combining mathematics education with psychological factors affecting student performance. The majority of his work centers on middle school mathematics education, examining variables like self-efficacy, problem-solving attitudes, and mathematical justification skills. He also maintains active research in statistical methodology, particularly in bootstrap methods and nonparametric techniques, demonstrating his dual expertise in both educational theory and quantitative analysis. TUBITAK Publication Incentive Award (2011) TUBITAK Publication Incentive Award (2012) Professor BINDAK has supervised 22 graduate theses (1 doctoral and 21 master's), reflecting his commitment to mentoring the next generation of researchers. His students have explored diverse topics within mathematics education, including mathematical connection self-efficacy, geometric justification skills, and the relationship between school climate and teacher burnout. His teaching portfolio spans doctoral, master's, undergraduate, and associate degree levels, with courses focused on statistics, probability, data analysis, and mathematical research methods. As evidenced by his extensive publication record and thesis supervision, Professor BINDAK maintains an active research laboratory focused on quantitative educational research, with particular attention to measurement theory, statistical methodology in education, and mathematics learning processes. His work continues to influence both educational practice and research methodology in Turkey's academic community.

• Quality Management
• Production and Service Systems Management
• Reliability Engineering
• +۲ مورد دیگر

Prof. Dr. Sezgin Çağlar Aksezer is a Full-Time Faculty Member in the Department of Industrial Engineering at Isik University's College of Engineering and Natural Sciences. His academic career spans over two decades, focusing on quality management, production systems, reliability analysis, and optimization techniques. PhD in Industrial Engineering (2003), Northeastern University MS in Industrial Engineering (2000), Northeastern University BS in Mathematics Engineering (1999), Yıldız Technical University His research emphasizes industrial systems optimization, particularly in corrective maintenance strategies, warranty modeling, and probabilistic graphical models for multi-component systems. He applies advanced statistical methods and dynamic frontier analysis to healthcare services and retail operations, bridging theoretical frameworks with real-world applications in thermal power plants, consumer electronics, and hospital efficiency. Key trends in his work include: Development of probabilistic graphical models for maintenance optimization Integration of Bayesian networks in complex system diagnostics Application of Data Envelopment Analysis (DEA) to evaluate institutional performance Exploration of Kano models and desirability functions for quality control He has supervised several graduate theses, including studies on credit evaluation processes, football league predictions, and customer expectation measurement methodologies. His teaching portfolio includes courses in Quality Planning, Production Operations, Reliability Analysis, and Applied Statistics since 2012.

• Stochastic inventory models
• Stochastic maintenance models
• Bayesian applications to inventory
• +۵ مورد دیگر

Prof. Dr. Ülkü Gürler is a Professor at Bilkent University with contactable office (EA314), email (ulku@bilkent.edu.tr), and telephone (+90 (312) 290 1520) details indicating active academic status. Her educational credentials include: Ph.D. in Statistics from the Wharton School, University of Pennsylvania (1990) M.S. in Statistics from the University of Pennsylvania (1987) B.S. in Applied Statistics from Middle East Technical University (1979) Prof. Gürler's research spans theoretical and applied statistics with emphasis on operational modeling. Her work integrates stochastic processes with real-world inventory and maintenance systems, while advancing methodological approaches for censored/truncated data through Bayesian and nonparametric frameworks. This creates synergies between reliability engineering and survival analysis methodologies. Her scholarly contributions focus on developing robust statistical solutions for complex industrial and biomedical data challenges, particularly where conventional parametric methods fail due to data limitations.

SEDAT AKTANمشاهده پروفایل

استاد

• Animal Science
• Nutrition
• Poultry Genetics
• +۵ مورد دیگر

SEDAT AKTAN is a Professor in the Department of Animal Science and Nutrition at the Faculty of Veterinary Medicine. His research focuses on poultry genetics, egg production, and digital image analysis applications in animal husbandry. Specializes in Japanese quail reproduction and egg quality analysis Expertise in genetic parameter estimation and statistical modeling Pioneered nonparametric regression studies in avian research Research Trends : Recent work emphasizes predictive modeling for egg production traits, hormonal effects on fertility, and genetic polymorphisms in layer chickens. His studies frequently utilize statistical tools like linear regression, MARS algorithm, and Theil regression. Leadership & Collaborations : Affiliated with the Ankara Poultry Research Institute and has contributed to European Association for Animal Production conferences.

• Econometrics
• Statistics
• Time Series Analysis
• +۷ مورد دیگر

Özge GÜNDOĞDU is a Lecturer at Süleyman Demirel University in the Department of Econometrics under the Faculty of Economics and Administrative Sciences. She also holds an affiliation with the Department of Statistics. Bachelor’s in Business Administration, Anadolu University (2013) Bachelor’s in Statistics, Ondokuz Mayıs University (2009) Bachelor’s in Management Information Systems, Anadolu University (2024) Master’s in Econometrics, Süleyman Demirel University (2011) Doctorate in Statistics, Ondokuz Mayıs University (2016) Her research focuses on econometrics, time series analysis, and machine learning applications in financial economics. She has developed innovative neural network models for forecasting economic and financial trends, such as stock prices and regional economic indicators. Recent publications highlight her work on Gaussian activation functions in artificial neural networks, robust regression for human development indices, and ensemble learning methods for stock exchange forecasting. She also explores LSTM models for evaluating football club share prices and nonparametric statistics in econometric modeling. She teaches courses including Time Series Analysis, Multivariate Statistical Analysis, Advanced Econometrics, and seminars on econometric models.

• Robust Statistics
• Statistical Modeling
• Multivariate Analysis
• +۵ مورد دیگر

Prof. Olçay Arslan is a Professor of Statistics at the Department of Statistics, Faculty of Science, Ankara University. He holds a Doctorate from the University of Leeds (1993) and has held academic positions including Associate Professor at Saint Cloud State University (2001-2003). His research focuses on robust statistical methods, multivariate analysis, and distribution theory with emphasis on heavy-tailed and skewed distributions. He has supervised 23 theses and published over 170 articles in peer-reviewed journals like Journal of Multivariate Analysis and Computational Statistics & Data Analysis . Education: PhD: University of Leeds, UK (1993) MSc: Ankara University (1986) BSc: Ankara University (1983) Key Roles: Head of Department (2014-2023) Member of University Academic Incentive Evaluation Commission (2016-present) Editorial Board member for multiple journals Research Interests: His work centers on robust statistical methodologies addressing outliers and non-normality in data. Notable areas include: Robust estimation techniques Mixture models and clustering Heavy-tailed distributions Regression analysis with autoregressive errors Computational statistics Recent Contributions: Recent studies emphasize: Variable selection in joint mean-covariance models Nonparametric tests for serial independence Robust methods for asymmetric/heteroscedastic data Applications of skew Laplace distributions Grants & Teams: Lead researcher on 4 funded projects. Active member of the Robust Statistics Research Group at Ankara University, collaborating on multidisciplinary data science initiatives.