جستجوی استاد راهنمای دانشگاهی

M. Tolga Akçuraمشاهده پروفایل

استاد

• Marketing Strategy
• Brand Valuation
• Consumer Behavior
• +۷ مورد دیگر

Professor Tolga Akçura is a distinguished faculty member at Özyeğin University's Faculty of Business, Department of Business Administration. With over 25 years of academic experience, he has developed and taught courses on marketing strategy, marketing analytics, and marketing research at prestigious institutions including Carnegie Mellon University, Purdue University, and Long Island University. At Özyeğin University, he teaches Marketing Strategy, Integrated Marketing Communication Strategies, Innovation, Business Model Development, and Advanced Topics in Marketing for undergraduate, graduate, and executive students. Professor Akçura holds a B.Sc. in Industrial Engineering from Boğaziçi University (1990), an MA in Business Administration from Boğaziçi University (1996), an MBA from Carnegie Mellon University (1998), and a Ph.D. in Quantitative Marketing from Carnegie Mellon University (2000). Before joining academia, he worked for Procter & Gamble across multiple European locations including Brussels, London, Manchester, and Istanbul. His research focuses on the intersection of Information Technology and Marketing, Brand Valuation, Consumer Learning Behavior, Structural Choice Models, Brand Equity dynamics, and Competitive Pricing Strategies. Professor Akçura has made significant contributions to marketing science through his extensive publication record in top-tier journals. His recent scholarly work demonstrates a strong trend toward digital marketing, AI applications in marketing analytics, healthcare marketing, and the strategic implications of data-driven decision making. His publications span from foundational work on brand equity to cutting-edge research on patient-generated health data and deep learning applications in campaign participation prediction. William W. Cooper Award (awarded twice for publications in Management Science and Marketing Science) Professor Akçura has successfully bridged academic research with practical business applications through his role as founder of eBrandValue A.Ş. and as a Y-Combinator alum (YCW15). He is an active member of professional organizations including the Institute for Operations Research and Management Science, American Marketing Association, and Direct Marketing Institute. His industry experience complements his academic work, providing students with valuable real-world insights into marketing strategy and implementation.

Mustafa Asım Kazancıgilمشاهده پروفایل

استادیار

• Web Design and Development
• Information Systems Security
• Big Data Analytics
• +۵ مورد دیگر

Mustafa Asım Kazancıgil is an Assistant Professor at Yeditepe University's Faculty of Computer and Information Sciences, Department of Information Security Technology. He has also served in the Department of Information Systems and Technologies at Yeditepe University since 2014. His academic journey includes a PhD in Informatics-Computer Science from Universita degli Studi di Milano (2013) and a Master's in Interactive Digital Television from the same institution (2006). PhD: Universita degli Studi di Milano (2013) Master's: Universita Degli Studi di Milano (2006) Bachelor's: Yeditepe University, Faculty of Communication, Department of Radio, Television and Cinema (2004) His research focuses on web design , information systems security , big data analytics , and emergency services technology . His publications include works on disaster resilience and interactive digital television applications. He has taught courses on Web Design, Information Systems Security, and Advanced Web Programming at both undergraduate and graduate levels. Administrative roles include Head of Department (2021) and multiple Erasmus Coordinator positions (2016-2019). He supervises theses in digital marketing and CRM trends, as well as CRM/SCM applications in management information systems. His teaching portfolio spans 2013-2025 across Yeditepe University's academic calendar.

• Computer Learning
• Fuzzy Sets and Systems
• Decision Support Systems
• +۳ مورد دیگر

Prof. Sadettin Emre Alptekin is a full Professor of Industrial Engineering at Galatasaray University, Faculty of Engineering and Technology, where he also serves as Vice Dean. Since joining the university as a research assistant in 2000, he has steadily advanced through the academic ranks, becoming an Assistant Professor (2006–2010), Associate Professor (2010–2023), and finally Professor in 2023. Education: PhD (Dr), Industrial Engineering, Istanbul Technical University, Institute of Science and Technology, 2001–2006 MSc, Industrial Engineering, Galatasaray University, Faculty of Engineering and Technology, 1999–2001 BSc, Industrial Engineering, Istanbul Technical University, Faculty of Management, 1995–1999 Languages: Advanced English (C1), Upper-Intermediate French (B2), Advanced German (C1) Research Interests: Prof. Alptekin’s research focuses on Computer Learning , Fuzzy Sets and Systems , and Decision Support Systems . His work integrates artificial intelligence, machine learning, and soft-computing techniques to solve complex industrial and managerial problems in areas such as supply chain management, quality function deployment, blockchain adoption, and mental-health prediction. Publication Trends: Across more than 50 refereed publications, Prof. Alptekin has consistently explored hybrid intelligent models that combine fuzzy logic, machine learning, and multi-criteria decision-making. Recent articles emphasize deep-learning-based anomaly detection in industrial time-series data, blockchain adoption in supply chains, and machine-learning applications in subjective well-being and mental-health modeling. Scientific Awards & Honors: No specific awards or medals are listed in the provided documents. Research Leadership & Funding: Since 2008 he has been the principal investigator (executive) of 12 nationally funded projects, covering topics such as Industry 4.0 sub-system design, Internet of Things applications, artificial neural networks in organizational decision-making, big-data analytics, and strategic decision processes. Graduate Advising: He has formally supervised at least 8 master’s theses and numerous undergraduate projects. Representative thesis titles include Gaussian-process-regression-based man-hour prediction, machine-learning-driven human-behavior modeling, recommender-system design for e-commerce, thyroid-nodule diagnosis from scintigraphic images, software-effort estimation via neural networks, spreadsheet heuristics for joint-replenishment problems, cross-selling decision systems in insurance, and profitability analyses of Turkish banks under disinflation. Laboratories & Teams: While no dedicated laboratory name is disclosed, his continuous role as Vice Dean and principal investigator implies active leadership of the Industrial Engineering department’s research clusters in intelligent systems and decision support technologies.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

• Civil Law
• Intellectual Property Law
• Information Law
• +۳ مورد دیگر

Mustafa Aksu is a Professor at Istanbul University's Faculty of Law, Department of Civil Law. His research spans Civil Law , Intellectual Property Law , Information Law , and EU Legal Harmonization . He has advised 26 theses and published extensively on digital rights, family law, and obligations law. Research Interests: Focus on AI and law, copyright exhaustion in digital markets, EU-Turkey legal alignment, domain name regulation, and protection of computer programs. Publications: Recent works include AI's legal frameworks (2023), medical informatics law (2021), and digital exhaustion doctrine (2016). His research emphasizes cross-border IP enforcement and EU court precedents. Contact: Email aksum@istanbul.edu.tr | Office: Hukuk Fakültesi Binası, İkinci Kat, Oda No: 38, Beyazıt, Istanbul, Turkey.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Prof. Dr. Mehmet Reşit Tolun is a full-time Professor in the Department of Software Engineering at Çankaya University (Turkey) since 2022. Previously held full-time professor positions at Konya Food and Agriculture University (2020-2022), Aksaray University (2013-2017), and TED University (2011-2013), along with a part-time professorship at Başkent University (2017-2020). Specializes in Artificial Intelligence , Machine Learning , and Data Mining , with a focus on deep learning applications in aerospace, biomedical data analysis, and software process improvement. PhD in Computer Science (University of Kent, 1985) MSc in Computer Science (University of Kent, 1982) BSc in Physics and Computer Science (University of Kent, 1981) Research Interests span deep learning frameworks, hybrid expert systems, software engineering methodologies, and biomedical signal processing. Publications emphasize practical implementations in medical diagnostics, robotics, and agricultural pest detection. Scientific Awards include the IEEE Third Millenium Medal (2000). Supervised over 55 graduate students, including Burak Çetin, Uğur Özotuk, and Mahinur Doğan. Collaborated with researchers from Orta Doğu Teknik Üniversitesi , Çankaya University , and Aksaray University .

Nuri Başoğluمشاهده پروفایل

استاد

• Decision Support Systems
• Information Systems Strategies
• Project Management
• +۷ مورد دیگر

Prof. Dr. Nuri Başoğlu is a Professor at Izmir Institute of Technology (IYTE). His educational background includes a BSc in Industrial Engineering from Boğaziçi University, and both MSc and PhD in Production Management from Istanbul University. Research Focus His research spans interdisciplinary domains with emphasis on: Technology Adoption : Healthcare systems, mobile services, and education. Innovation Processes : Sociotechnical systems, product design, and decision support. Information Systems : Strategic implementation and human-computer interaction. Recent publication trends (2010–2013) highlight technology diffusion in healthcare, including telemedicine, health informatics, and e-learning. Cross-cultural studies on mobile services and ERP optimization in manufacturing also feature prominently. No awards, grants, or supervised students are documented in the provided materials.

• Bioinformatics
• Computational Biology
• Protein Informatics
• +۳ مورد دیگر

Barış Ethem Süzek is an Associate Professor in the Department of Computer Engineering at the Faculty of Engineering, Muğla Sitki Koçman University. His academic career spans institutions including Middle East Technical University (BS), Johns Hopkins University (MS), and George Mason University (PhD) in Computational Biology. He specializes in bioinformatics and computational biology, focusing on protein informatics, genetic analysis, and machine learning applications in medical research. Education BS: Middle East Technical University - Computer Engineering (1997) MS: Johns Hopkins University - Computer Science (2000) PhD: George Mason University - Computational Biology (2012) His research integrates bioinformatics with molecular dynamics, particularly in host-pathogen interactions, regenerative medicine, and genomic data analysis. He has developed machine learning tools for viral interaction prediction and variant analysis systems. His work with UniProt and cancer Biomedical Informatics Grid projects demonstrates expertise in large-scale biological data integration. Scientific awards include Collaboration, Outstanding Achievement, and Change Agent Awards from the cancer Biomedical Informatics Grid, plus multiple patent recognitions for biomedical systems. He has supervised numerous graduate students in bioinformatics, computational genetics, and forensic biology projects.

• Artificial Intelligence
• Medical Imaging
• Deep Learning
• +۳ مورد دیگر

Caner Özer is a Researcher affiliated with Istanbul Technical University's Department of Artificial Intelligence and Data Engineering and the University of Twente's MIA group. He holds a PhD in Computer Engineering from Istanbul Technical University (2020), an MSc in Telecommunication Engineering (2017-2020), and a BSc in Electronics and Communications Engineering (2013-2017). His research focuses on medical imaging AI, explainable artificial intelligence (XAI), deep learning applications in healthcare, and computer vision techniques for artifact detection in medical imaging. He has conducted visiting research at the University of Twente (2024) and serves on academic committees at Istanbul Technical University. Research interests include developing explainable models for mammogram analysis, enhancing medical image quality assessment via transformers and neural networks, and addressing challenges in cardiovascular MRI segmentation through motion artifact detection. His work bridges deep learning theory with practical clinical applications, emphasizing transparency and accuracy in AI-driven medical diagnostics. Notable contributions include cross-domain artifact correction for cardiac MRI, joint CNN-RNN models for intracranial hemorrhage detection, and XAI methods for chest X-ray analysis. His research has been published in top-tier venues with a focus on medical imaging and deep learning advancements.

• Biostatistics
• Statistical Analysis
• Applied Statistics
• +۵ مورد دیگر

Professor Ufuk Karadavut serves at Karabük University Faculty of Medicine, Department of Basic Medical Sciences, where he holds the position of Professor and currently serves as Vice Dean. Previously, he was Dean of the Faculty of Medicine from 2021-2022 and has held multiple leadership roles including Head of Department since 2020. With an extensive publication record of 493 works and significant contributions to both medical and agricultural statistics, his career spans multiple Turkish universities including Ahi Evran University and Bingöl University. PhD, Selçuk University, Institute of Science (2001-2005) Bachelor's Degree, Ankara University, Faculty of Agriculture, Department of Animal Science (1987-1991) Professor Karadavut's research spans biostatistics, medical informatics, and agricultural statistics, with particular expertise in statistical experimental design. His work bridges healthcare applications (medical informatics, clinical data analysis) with agricultural science (crop breeding, animal husbandry). He has developed statistical methodologies applicable across diverse fields, from analyzing palliative care outcomes to optimizing chickpea breeding programs for drought tolerance. His research demonstrates a consistent pattern of applying advanced statistical techniques to solve practical problems in both medical and agricultural contexts. Analysis of his recent publications reveals a strong focus on applying statistical methodologies to address contemporary challenges. In medical informatics, he examines healthcare quality, medical education, and pandemic impacts. In agricultural science, his work centers on crop improvement (particularly chickpeas and other legumes) and animal breeding. His statistical approaches include multivariate analysis, QTL mapping, growth modeling, and machine learning techniques, demonstrating methodological versatility across disciplinary boundaries. While specific awards aren't detailed in the available information, his h-index of 11 (UNIS) and 8 (WoS), along with 583 total citations, indicate significant scholarly impact. His research has attracted funding from major Turkish research bodies including TÜBİTAK and university-supported projects. Professor Karadavut has supervised 13 theses across multiple institutions and taught diverse courses ranging from medical bioinformatics to agricultural statistics. His research portfolio includes 31 projects, with recent work focusing on climate change adaptation in livestock, medical informatics applications, and advanced statistical methodologies for agricultural research. He has collaborated extensively with researchers across multiple Turkish institutions, demonstrating strong interdisciplinary networking capabilities.

• Information Security and Reliability
• Cyber Security
• Artificial Intelligence
• +۱۳ مورد دیگر

Prof. Dr. Murat Dener is a full Professor in the Department of Information Security Engineering at the Institute of Science and Technology, Gazi University, where he also serves as the Head of Department since 2020. He has been continuously affiliated with Gazi University since 2005, progressing from Research Assistant to full Professor in 2023. He is also a Member of the Gazi University Rectorate Quality Commission and a Researcher at the High Performance Computational Neuroscience Laboratory at the Neuroscience and Neurotechnology Excellence Joint Application and Research Center. His educational background includes a BSc, MSc, and PhD, all from Gazi University, with his doctoral studies partially conducted at Georgia Tech University, USA. He completed English language training at Georgia State University and has participated in multiple EU-funded international projects across Greece, Portugal, Belgium, Germany, and Kazakhstan. His research focuses on cutting-edge areas such as cyber security, artificial intelligence, internet of things, blockchain, big data analytics, and computational neuroscience. His work bridges theoretical research with practical innovation, exemplified by the development of Turkey’s first domestically produced wireless sensor node, "WiSeN", through a company he founded in 2014. The analysis of his recent publications reveals a strong trend toward integrating AI and deep learning into cyber defense, secure IoT systems, blockchain applications, and computational neuroscience. His work emphasizes real-world applicability, security, scalability, and innovation in smart city and critical infrastructure technologies. Academic Achievement Award, Georgia State University (2011) Second Prize, Gazi University Business Idea Competition (2014) Turkish First Prize, Junior Chamber International 'Ten Successful Young People of Turkey' (2014) World Top 20 Finalist, Junior Chamber International (Japan, 2014) First Prize, Young Entrepreneurship Category, Liyakat Association (2015) First Prize, Smart Buildings and Environment, TET R&D Project Market (2018) Prof. Dener actively advises master’s and doctoral students and has led numerous national and international research projects, including EU-funded collaborations. His leadership extends to editorial and peer-review roles in multiple journals. He is deeply involved in academic quality improvement as a member of the Rectorate Quality Commission and leads advanced research in computational neuroscience using high-performance computing platforms. He founded a technology company in 2014 under the Technopreneurship Capital Support Program, producing the first Turkish-made wireless sensor node (WiSeN), which led to several national innovation awards. His lab work centers on the High Performance Computational Neuroscience Laboratory, where he contributes to neurotechnology research, combining AI and neuroscience for brain-computer interface applications.

Yeşim AYDIN SONمشاهده پروفایل

استادیار

• Bioinformatics
• Translational Bioinformatics
• Personalized Medicine
• +۵ مورد دیگر

Assist. Prof. Dr. Yeşim AYDIN SON is a faculty member at Middle East Technical University (METU) Informatics Institute, Health Informatics Department, with a focus on translational bioinformatics and personalized medicine. She leads the METU Bioinformatics Graduate Program and has developed innovative software tools like METU-SNP and pi-SNP for genomic research. Education: MD from Hacettepe University Medical School, PhD in Genome Sciences & Technology from University of Tennessee, Knoxville Key Roles: Chair of Health Informatics Department, former Bioinformatics Program Coordinator Research Collaborations: University of Barcelona, European Institutes Her research integrates genomics and environmental data to advance clinical applications under P4 Medicine (Preventive, Predictive, Personalized, Participatory). She emphasizes translating bioinformatics findings into clinical decision support systems. She has received recognition for her work, including awards at the iGEM competition and funding through METU BAP, TUBITAK 1001, and Teknogirişim programs. Her team transformed the METU-SNP desktop application into a web-based platform and co-developed the M4B software for synthetic biology design. Scientific contributions include: Development of METU-SNP/pi-SNP for SNP-disease association analysis Leadership in FP7 project on chronic disease prediction via probabilistic methods Co-instruction of METU-BIN Software Team at iGEM

• Artificial Intelligence
• Natural Language Processing
• Computational Linguistics
• +۶ مورد دیگر

Ayşenur Akyüz Birtürk serves as a Lecturer in the Department of Computer Engineering at Middle East Technical University (METU), Ankara, where she has taught since February 1994. Her academic career spans foundational programming courses to advanced graduate seminars in AI and Computational Linguistics, reflecting 30+ years of institutional commitment. She earned all her degrees from METU, culminating in a 1998 Ph.D. focused on Turkish language computational analysis. Her educational journey includes: B.S. in Computer Engineering (1985) M.S. in Computer Engineering (1988) with thesis on “A Model for Representing Concepts: Conceptual Dependency Theory” Ph.D. in Computer Engineering (1998) with thesis on “A Computational Analysis of Turkish using the Government-Binding Approach” Dr. Birtürk’s research centers on Artificial Intelligence and Natural Language Processing , with pioneering work in Turkish language parsing evolving into modern Recommender Systems . She integrates semantic relations and multi-domain data to build hybrid engines for movies, books, and music, emphasizing user modeling through knowledge representation and data mining techniques. Analysis of her 2010-2015 publications reveals two dominant threads: adaptive recommender systems (80% of output) using semantic similarity and dynamic clustering, and renewable energy analytics (20%) applying machine learning to wind/hydrological data. This pivot from NLP to energy forecasting demonstrates methodological versatility while maintaining core AI expertise. Her scientific recognition includes: TUBITAK scholarships throughout education (1977-1988) Multiple national contest awards in high school (1979-1980) Leadership in TUBITAK-funded energy and healthcare projects Dr. Birtürk has supervised 17 Master’s theses in NLP and recommender systems while securing competitive grants including METU-ISTEC #17435 (2006-2008; 504,000 YTL) and HASAT (2010-2013; 601,637 YTL). Her industry consultancy spans medical form design (FormAnalitik), question-answering systems, and retail intelligence platforms, translating academic research into real-world tools.

• Health Economics and Policy
• Health Management
• Critical Theory
• +۴ مورد دیگر

Assoc. Prof. Dr. Rukiye ÇELİK serves as Associate Professor in the Department of Public Relations and Promotion at Suleyman Demirel University's Faculty of Communication. Her academic trajectory spans health administration and critical communication studies, with active scholarly contributions through 2023. Current research focuses on the sociocultural dimensions of health discourse and institutional power structures. Her educational foundation includes: Associate Degree in Oral and Dental Health from Istanbul University (2006) Licence in Health Administration from Hacettepe University (2010) Master's Degree in Health Management (Thesis) from Suleyman Demirel University (2012) Doctorate in Health Institutions Administration from Suleyman Demirel University (2016) ÇELİK's research critically examines health communication through lenses of biopower, medicalization, and cultural representation. She investigates how health discourse shapes societal norms, analyzing phenomena from anti-aging advertising to health anxiety in digital environments. Her work consistently bridges critical theory with empirical studies of healthcare systems and media practices, emphasizing power dynamics in health literacy and policy implementation. Publication analysis reveals evolving thematic priorities: early work (2012-2016) focused on healthcare administration and institutional identity, while recent output (2018-2019) addresses urgent communication challenges including mobile health security, hubris in medical professions, and political hashtag activism. This progression demonstrates increasing engagement with digital media's impact on health perception and policy. No scientific awards were documented in the provided materials. The available information contains no references to graduate student supervision, research grants, or laboratory affiliations. Her advisory roles and funded projects remain unreported in the current documentation.

BÜLENT HAZNEDARمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Fuzzy Logic
• +۵ مورد دیگر

Bülent Haznedar is an Associate Professor in the Department of Computer Engineering at Gaziantep University's Faculty of Engineering, a position he has held since 2024. Previously, he served as Doctor Lecturer at Gaziantep University (2021-2024) and held academic positions at Hasan Kalyoncu University (2013-2021) and Erciyes University (2011-2013), where he progressed from Lecturer to Department Head. His educational qualifications include: Doctorate in Computer Engineering from Erciyes University (2011-2017) Master's degree in Computer Engineering from Erciyes University (2007-2010, with thesis) Licence degree in Computer Engineering from Erciyes University (2003-2007) Dr. Haznedar's research centers on Artificial Intelligence and Machine Learning applications, with significant contributions in hydrological modeling (streamflow forecasting using hybrid ANFIS algorithms), renewable energy (solar radiation optimization), medical diagnostics (thyroid nodule classification and cancer detection), and cultural heritage informatics (3D point cloud segmentation for historical buildings). His work consistently integrates fuzzy logic systems with metaheuristic optimization techniques to solve complex prediction problems. Analysis of his 29 journal articles (2016-2024) reveals a dominant focus on Adaptive Neuro-Fuzzy Inference Systems enhanced by evolutionary algorithms (PSO, GA, ABC) across hydrology and medical domains, with recent expansion into sustainable energy and heritage preservation. His publications show increasing interdisciplinary collaboration, particularly in TUBITAK-funded projects. His scientific recognition includes: TUBITAK Publication Encouragement Awards (2018, 2023) TUBITAK PhD Scholarship (2011) TUBITAK Master's Scholarship (2008) Dr. Haznedar has supervised eight master's theses on AI applications in streamflow forecasting, energy prediction, cancer classification, and heritage modeling. His research is supported by seven projects, most notably the TUBITAK 1001 project (2019-2023) developing Heritage Building Information Modeling for Turkey's cultural heritage restoration. He also contributed to TUBITAK's Digital Prosthesis Workshop initiative. While specific laboratory affiliations aren't detailed, his leadership in the TUBITAK cultural heritage project indicates active collaboration with multidisciplinary teams spanning engineering, computer science, and heritage conservation disciplines.