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.
Gül GÜLER is an academic researcher specializing in educational measurement and psychometrics. Holding a doctoral degree, her work focuses on scale development, factor analysis, and educational technology. Bachelor's Degree (2008) Master's Degree (2012) Doctoral Degree (2017) Her research interests include: Educational measurement and assessment design Psychometric evaluation of scales Factor analysis in skewed distributions Collaborative learning tools for gifted students Teacher education and professional identity Dimensionality analysis in educational testing Key publications examine wording effects in scales, reliability testing, and bibliometric trends in educational research. She has contributed to projects like the TÜBİTAK 4004 science outreach initiative and Istanbul Governorship's life skills training program.
Selin Aslan serves as an Assistant Professor in the Department of Mathematics at Koç University, Istanbul, Turkey, where she conducts research at the intersection of computational mathematics and imaging science. Her academic appointments and research activities are centered within the university's mathematics department, contributing to both undergraduate and graduate education in mathematical sciences. Her educational qualifications include: PhD in Mathematics from Virginia Polytechnic Institute and State University (2018) Master's in Mathematics from Rochester Institute of Technology (2013) B.A. in Mathematics from Ege University (2010) Dr. Aslan's research program focuses on developing advanced computational methods for solving inverse problems in imaging, with particular expertise in phase retrieval, tomographic reconstruction, and ptychography. Her work bridges theoretical mathematics with practical applications in medical imaging, microscopy, and materials science, emphasizing algorithmic innovation and computational efficiency. She integrates techniques from deep learning, optimization theory, and high-performance computing to address challenges in image reconstruction under physical constraints. Analysis of her publication record reveals a consistent trajectory toward solving complex imaging problems through hybrid approaches that combine physics-based models with data-driven techniques. Her recent work demonstrates increasing emphasis on scalability for large datasets, robustness in photon-limited scenarios, and real-time processing capabilities, with applications spanning biomedical imaging to advanced microscopy. No scientific awards were documented in the available sources. Information regarding student advising and research grant activities was not specified in the provided materials, though her publication record suggests active research collaboration. Her computational focus implies engagement with high-performance computing resources for large-scale image reconstruction tasks. While specific laboratory infrastructure details were unavailable, her research on multi-GPU implementations and distributed computing indicates utilization of advanced computational facilities for handling large-scale imaging datasets.
Hakan AYDOĞAN is an Assistant Professor in the Department of Forest Industry Engineering at the Faculty of Forestry, Kastamonu University, Turkey, where he also serves as Institute Deputy Director since 2023. Previously, he worked as a Research Assistant at the same institution from 2015-2022. His educational background includes: PhD in Quantitative Methods from Marmara University (2017-2022) Master's Degree in Business Administration from Brunel University, England (2013-2014) BSc in Forest Industry Engineering from Bartın Faculty of Forestry, Bülent Ecevit University (2005-2009) Dr. Aydoğan's research focuses on Forest Industry Management, with particular emphasis on optimization techniques, statistical quality control, and time series analysis in the wood products industry. His interdisciplinary work bridges forestry engineering with business administration, applying quantitative methods to solve industry challenges. His publication record demonstrates strong expertise in predictive modeling, particularly using artificial neural networks and regression methods for industrial applications. His scholarly impact is reflected in citation metrics: 54 citations and h-index of 4 in Google Scholar. His research spans wood product manufacturing, economic growth analysis, heat transfer prediction, and statistical quality control methods, with a recent shift toward renewable energy applications in forestry. Scientific recognition: YLSY Scholarship (1416 Law) from Ministry of National Education (2010) Faculty and Department First Place Plaket from Bartin University (2009) Dr. Aydoğan has successfully led multiple research projects including TÜBİTAK-funded initiatives on data analysis methods in forestry (2023) and thesis proposal training for graduate students (2024). He has established a robust research network with 16 collaborators, most frequently working with Osman Emre Özkan, Mustafa Öncel, and Hasan Vurdu. His teaching portfolio includes graduate courses in Optimization Techniques, Statistical Quality Control, and Advanced Statistics in Forest Industry, alongside undergraduate courses in Production Planning, Operations Research, and Investment Planning.
Idriss Dagal serves as an Assistant Professor at Beykent University's Department of Electrical and Electronics Engineering. With a PhD and Master's in Electrical Engineering from Yildiz Technical University (2015 and 2023 respectively), and additional academic credentials from Ethiopian Airlines Aviation University and Mongo Polytechnics University, his career bridges academic research with industry experience as a Sales Engineer. PhD: Yildiz Technical University (2015) Master's: Yildiz Technical University (2023), Ethiopian Airlines Aviation University (2008) Bachelor's: Mongo Polytechnics University (2006) His research focuses on renewable energy systems , particularly photovoltaic power optimization using metaheuristic algorithms (Hybrid PSO-Salp Swarm, Gray Wolf Optimization). He also explores control systems for solar energy and aircraft dynamics, including PID and fuzzy logic controllers. Additional work spans machine learning applications in energy and medical diagnostics, along with power electronics for battery charging. Recent publications highlight 15 2025 articles on topics like hybrid energy systems , AI-driven MPPT , and aircraft control frameworks . His work appears in journals such as Scientific Reports , IEEE Access , and International Journal of Aeronautical and Space Sciences . Teaching experience includes courses in Electrical Machines and Information Technologies . Non-university roles at Elektra Electronic Company and Aktif Group Company involved sales engineering, complementing his academic profile with industry insights.
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.
Dr. Emrah Ahi is an Assistant Professor of Finance at Özyeğin University's Faculty of Business Administration and a researcher at the Center for Financial Engineering. With over 15 years of experience in finance, he previously served as a fund manager at HSBC Global Asset Management. PhD in Finance (Özyeğin University, 2010-2016) MS in Computational Science and Engineering (Koç University, 2004-2007) BSc in Mathematics (Middle East Technical University, 2000-2004) His research spans fixed income securities, derivatives, asset pricing , and machine learning , with cross-disciplinary contributions to peer-to-peer network protocols and distributed systems . Key themes include risk modeling, volatility analysis, and robust computational methods in finance, alongside technical innovations in gossip-based data dissemination. Recent publications focus on volatility smile modeling in currency options, term structure estimation in emerging markets, and applying machine learning to credit risk analysis. Earlier work on buffer management in epidemic algorithms demonstrates methodological rigor in distributed computing. He teaches courses in Applied Financial Economics, Derivatives, Fixed Income Markets, and Investments. His affiliations include Özyeğin University's Center for Financial Engineering and collaborations in computational finance research.
Naciye Sündüz OĞUZ serves as an Assistant Professor at Kastamonu University's Araç Rafet Vergili Vocational School in the Medical Services and Techniques Department since 2025. Previously, she held lecturing positions at Pamukkale University's Faculty of Architecture and Design (2023-2024) and Kastamonu University's Vocational School in Textile, Clothing, Footwear and Leather Department (2012-2025), while also serving as Deputy Director of the Vocational School (2024-2025) and Department Head (2019-2021). Her academic credentials include a PhD in Textile Engineering from Süleyman Demirel University (2019) focusing on radiation-shielding antibacterial fabrics, a Master's degree from the same institution (2012) examining radiation effects on antibacterial properties, and a Bachelor's degree in Textile Engineering from Kahramanmaraş Sütçü İmam University (2009). She maintains proficiency in English with a ÜDS score of 66 (2010). Dr. OĞUZ specializes in Technical Textiles with concentrated expertise in radiation-shielding and antibacterial applications. Her research integrates nanotechnology, functional finishes, and statistical methods to develop advanced medical and protective textiles. She has pioneered work on silver nanoparticle coatings, gamma radiation effects, and Taguchi methodology for textile quality optimization, establishing herself at the intersection of textile engineering and biomedical applications. Her publication portfolio demonstrates consistent focus on radiation protection and antibacterial textile technologies, with recent work emphasizing medical applications of technical textiles and nanosilver-enhanced functionality. The 2023-2024 publications particularly highlight gamma radiation shielding properties and nanosilver applications in woven fabrics, reflecting her ongoing commitment to protective textile innovation. She secured research funding for the project 'Effect of radiation rays on the antibacterial properties of fabrics' (2011-2012) and has maintained significant collaborations with Feyza Akarslan Kodaloğlu (4 publications) and Mehmet Dayık (4 publications). Throughout her career, Dr. OĠUZ has taught diverse vocational courses including Textile Technology, Mathematics, Foreign Language, and specialized subjects like Nanotechnology and Smart Textiles, demonstrating comprehensive pedagogical engagement across engineering and medical domains.
Prof. Dr. Tufan Kumbasar is a faculty member at the Department of Control and Automation Engineering , Istanbul Technical University , where he has served as a Professor since 2024. He previously held roles as Associate Professor (2019-2024), Vice Dean (2017-2020), and Guest Professor at the University of Alaska Fairbanks (2016). His research spans multiple domains in computational intelligence and control systems. PhD in Control and Automation Engineering (ITU, 2012) Postdoctoral Research (University of Essex, 2012) Master's and Bachelor's in Control and Automation Engineering (ITU, 2008 and 2006) His work focuses on Type-2 Fuzzy Logic Systems , Deep Learning Integration , and Uncertainty Quantification with applications in Drone Swarms , Autonomous Vehicles , and Medical Robotics . Recent publications highlight hybrid control methodologies combining conventional and fuzzy logic, AI-driven system identification , and real-world implementations of learning frameworks. 2023 BAGEP Science Academy Young Academician Achievement Award 2022 IEEE Türkiye Outstanding Young Scientist Award 2021 Parlar Foundation Research Encouragement Award Best Publication Awards (2015, 2018) As a Principal Investigator , he leads projects like KAYRA Search and Rescue Robot and UMAY Search and Rescue Robot , emphasizing Deep Learning-based Type-2 Fuzzy Systems and Reliable Uncertainty Quantification . His teaching innovations include transforming Feedback Control Systems into MATLAB environments via Deep Learning Pipelines .
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.
Atilla HEPKORUCU serves as a full-time Lecturer at Kastamonu University's Taskopru Vocational School within the Banking and Insurance Program. With over a decade of academic service since 2011, his career spans teaching 21 distinct courses including Financial Management, Portfolio Management, Risk Management, and Financial Markets. His educational background includes a PhD in Econometrics from Bursa Uludağ University (2012-2020), a Master's in Finance from Dokuz Eylül University (2008-2010), and a BSc in Food Engineering from Ege University (2003-2008). His research focuses on advanced econometric methodologies applied to financial markets and economic indicators. HEPKORUCU's scholarly work centers on time series analysis and econometric theory, particularly developing and testing novel unit root methodologies. His research examines nonlinear reversion patterns, seasonal unit roots, and structural breaks in financial time series data. Recent publications analyze cryptocurrency markets (especially Bitcoin), consumer confidence indices across G-7 nations, and tourism revenue dynamics. His publication portfolio includes 25 total works comprising 11 journal articles, 12 conference papers, and 2 book chapters. Notable contributions include developing the Fourier-Sollis unit root test and analyzing volatility breaks in low-frequency financial assets. His work appears in journals such as ESKISEHIR OSMANGAZI UNIVERSITY JOURNAL OF ECONOMICS AND ADMINISTRATIVE SCIENCES and Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. HEPKORUCU collaborates extensively with researchers including Öznur Doğan, Mehmet Çınar, and Sevdanur Genç across institutions like Uludağ University and Dokuz Eylül University. His metrics show a Google Scholar h-index of 5 with 104 citations, reflecting significant impact in econometrics methodology development.
Dr. Serkan Saritas is an Assistant Professor in the Department of Electrical and Electronics Engineering at Middle East Technical University (METU). He holds a Ph.D. from Bilkent University (2018) and completed postdoctoral research at KTH Royal Institute of Technology in Sweden (2018–2021). His research focuses on Networked Control Systems, Game Theory applications in security, Communication Theory, and Information Theory. He has authored numerous high-impact publications in top-tier venues such as IEEE Transactions on Automatic Control, IEEE Transactions on Information Theory, and Automatica. Education: Ph.D. in Electrical and Electronics Engineering, Bilkent University (2013–2018) M.Sc. in Computer Engineering, Bilkent University (2010–2013) B.Sc. in Electrical and Electronics Engineering, Bilkent University (2005–2010) Research Interests: Game-Theoretic Security (e.g., adversarial attacks, authentication strategies) Networked Control Systems (resilience, fault tolerance) Information Theory (signaling games, estimation theory) Communication Theory (channel modeling, detection algorithms) Awards: Recipient of the IEEE Turkey PhD Thesis Award (2020), TÜBİTAK scholarships for graduate studies, and top national exam rankings (1st in ALES 2014, 2nd in ÖSS 2005). Teaching: Recently taught courses like EE348 (Logic Design) and EE494 (Engineering Design) at METU.
Professor Ahmet Duran at Istanbul Technical University's Department of Mathematics specializes in applied mathematics with interdisciplinary applications in renewable energy systems, financial mathematics, and computational modeling. His research focuses on differential equations, numerical methods, and optimization techniques. Current projects involve EU collaborations on supercomputing (GPGPU for bio-fluid applications) and sparse direct solvers for linear equations. Recent publications emphasize wind/solar energy prediction, climate resilience, and financial portfolio optimization via principal component analysis. Technical expertise spans spectral analysis, fuzzy logic modeling, and high-performance computing using frameworks like SuperLU.
Mehmet Onur KAYA is an Associate Professor and Head of the Department of Biostatistics and Medical Informatics at Fırat University Faculty of Medicine in Elazığ, Turkey. He previously served as a Lecturer at Bezmialem Vakıf University Faculty of Medicine in Istanbul (2013–2017) and as a Research Assistant at Uludağ University Faculty of Medicine (2013–2014). He completed his Doctorate in Biostatistics at Uludağ University between 2013 and 2016. His research interests are centered on biostatistics and medical informatics, with a strong focus on epidemiological and clinical applications. Key areas include vitamin D deficiency in pregnancy and its public health implications, glycemic control in type 2 diabetes, cardiovascular complications in hemodialysis patients, stroke imaging, and statistical methodology in medical and veterinary research. He has contributed to studies on hidden curricula in medical education during the pandemic and the impact of passive smoking on pediatric respiratory health. The recent publication trends indicate a strong engagement in systematic reviews and meta-analyses, particularly concerning vitamin D and COVID-19, as well as robust use of statistical analysis in neuroimaging and public health studies. His work frequently involves collaboration with multidisciplinary teams across various medical specialties. Scientific Contributions: Active researcher with numerous publications in journals such as Journal of the College of Physicians and Surgeons Pakistan , Current Medical Imaging , Epidemiology and Health , and World Neurosurgery . Peer reviewer for Heliyon . Advising and Grants: While no specific students or grant funding are mentioned in the provided text, his role as Head of Department and frequent collaboration suggests leadership in research supervision and project coordination. Laboratories and Research Teams: No specific labs or dedicated research teams are mentioned, but his collaborative work indicates active participation in various research groups across institutions.
Assoc. Prof. Fulya Gökalp Yavuz is a faculty member at the Department of Statistics within the College of Science at Middle East Technical University (METU), Ankara, Turkey. Her academic career spans roles as a Research Assistant at Yildiz Technical University (2010-2019), Statistical Consultant at Purdue University (2008-2009), and Post-Doc Researcher in Statistics at Purdue University (2016-2017). Education: PhD in Statistics (Yildiz Technical University, 2015), M.S. in Statistics (Purdue University, 2010), B.S. in Statistics (Hacettepe University, 2006) Her research focuses intersect statistical theory and computational methods, including Linear Mixed Models, Robust Distributions, Parallel Programming, and Machine Learning. She also contributes to statistical applications in big data, cognitive neuroscience, and environmental science, with a strong emphasis on R programming and reproducible research practices. Her recent publications highlight advancements in parallel computing for kernel regression, hybrid modeling of neuroimaging data, and robust estimation techniques in multivariate regression. These works align with keywords in statistical computing, neuroscience, and data science. Scientific Awards: International Post Doctoral Research Fellowship (TUBITAK), Best Presentation awards at ICS 2017 and IC-SMHD-2016, Course Honorarium at ASA 2018 She actively engages in academic leadership as Project Coordinator for METU's Data Science Ecosystem (2019-2021) and collaborates on TUBITAK-funded research, including pandemic data modeling and cultural heritage regeneration projects.
