جستجوی استاد راهنمای دانشگاهی

• Natural Language Processing
• Computational Linguistics
• Dependency Parsing
• +۳ مورد دیگر

Prof. Dr. Gülşen Eryiğit is a Professor at Istanbul Technical University within the Faculty of Computer and Informatics , Department of Artificial Intelligence and Data Engineering . She founded and directs the ITU Natural Language Processing Group , Turkey's leading team in Turkish-language NLP, and serves as Senior Action Editor for ACL RR , Director of ITU TÖMER (Turkish Language Teaching Center), and Co-Chair of the EU UniDive Cost Action WG3. Education: PhD in Computer Engineering from ITU (2007), MSc and BSc from ITU and Marmara University Research: Focuses on Natural Language Processing for Turkish, including dependency parsing , coreference resolution , multiword expressions , and language education technology Her recent work involves multilingual transfer learning , LLM applications for Turkish text simplification, and gamification for morphology education. She has received prestigious awards like the Siemens Excellence Award and TÜBİTAK's Above Threshold Award . Her research has produced 65+ publications and 29+ projects funded by EU, TÜBİTAK, and industry partners. Scientific Awards: Siemens Excellence Award (2007) Above Threshold Award (TÜBİTAK, 2015) Certificate of Appreciation (EU 7th Framework, 2012) Thank You Plaque (ITU, 2017) The ITU NLP Group under her leadership has developed Turkey's first licensed NLP software exported internationally. She collaborates with European institutions through COST actions and participates in ACL, CoNLL, and LREC conferences. Her lab focuses on language technology for Turkish , including sign language processing and social media normalization.

ABDULBAKİ ÇETİNمشاهده پروفایل

استاد

• Ottoman Turkish Literature
• Historical Linguistics
• Turkic Manuscripts
• +۳ مورد دیگر

Prof. Dr. ABDULBAKİ ÇETİN is a Professor of Turkish Language and Literature at Bingöl University's Faculty of Arts and Sciences. He holds a PhD from Atatürk University (2002) and has taught extensively since 2002. His current courses include Ottoman Turkish III/IV, Old Anatolian Turkish, and Chagatai Text Studies. He has supervised three doctoral theses focusing on medieval manuscripts and literary works. Licentiate: Atatürk University (1991-1995) Master's: Atatürk University (1996-1998) Doctorate: Atatürk University (1998-2002) His research focuses on pre-modern Turkic texts, Ottoman Turkish linguistics, and medieval Islamic manuscripts. He has published widely on topics like Persian grammar in Anatolia, Ottoman translations of classical texts, and Sufi literary traditions. Recent work includes analyses of 15th-17th century manuscripts and lexicographical studies. Prof. Çetin has authored/co-authored three books and contributed chapters on medieval Turkic scholars and literary works. His published articles span over two decades, with significant contributions to journals like Atatürk Üniversitesi Türkiyat Araştırmaları Enstitüsü Dergisi and Selçuk Üniversitesi Türkiyat Araştırmaları Dergisi.

• Natural Language Processing
• Text Normalization
• Named Entity Recognition
• +۵ مورد دیگر

Dilara Torunoğlu Selamet serves as a Lecturer in the Department of Computer Engineering within the Faculty of Computer and Informatics at Istanbul Technical University. Holding a PhD, she specializes in Natural Language Processing for Turkish, with research emphases on social media text normalization, named entity recognition, and sentiment analysis. Her academic credentials feature: PhD in Computer Engineering, Istanbul Technical University (awarded circa 2013) Master of Science in Computer and Information Sciences (Non-thesis), Doğuş University (2009-2013) Bachelor of Science in Computer Engineering, Doğuş University (2004-2009) Dilara's scholarship tackles the complexities of Turkish NLP, a language with rich morphology. She has made notable contributions to text normalization for social media platforms, named entity recognition in authentic datasets, and semantic smoothing techniques for sentiment classification. Her work often bridges theoretical NLP with practical applications, as seen in resource-building projects like the ITU Web Treebank and Turkish sign language corpora. Her publication record (2011-2021) demonstrates methodical growth: initial work on text classification (2011) evolved into named entity recognition (2013) and social media normalization (2014, 2017), then expanded to data augmentation (2020-2021) and sign language processing (2020). This trajectory reflects her commitment to advancing Turkish NLP through both foundational research and innovative resource development. While no specific awards are documented, her research impact is evidenced by an h-index of 4 and over 127 citations in Scopus. Available information does not indicate any students supervised or research grants obtained. She is affiliated with Istanbul Technical University's Department of Computer Engineering, but no laboratory or research team memberships are specified in public profiles.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۱۲ مورد دیگر

Ahmet Cüneyd Tantuğ is an Associate Professor in the Department of Artificial Intelligence and Data Engineering at the Faculty of Computer and Informatics, Istanbul Technical University (ITU). He has been a core faculty member since 2007 and is among the founders of the ITU Natural Language Processing Group. He has held key administrative roles, including Vice Dean (2011–2015) and Head of IT Department at ITU (2012–2020). BSc, MSc, PhD: Istanbul Technical University, Computer Engineering Guest Researcher: University of Copenhagen, Centre for Language Technology (2006–2007) Dr. Tantuğ’s research spans artificial intelligence, natural language processing, machine learning, and deep learning, with a focus on Turkish and other agglutinative languages. His work includes named entity recognition, dependency parsing, machine translation, word sense disambiguation, and text normalization. He has developed linguistic resources for Turkish and low-resource languages such as Amharic, and has contributed to financial AI and temporal expression extraction. His recent publications highlight advancements in Turkish NLP, including optimal vocabulary sizing, tokenization granularity for LLMs, and transformer-based models for named entity recognition. He has led multiple research projects funded by TÜBİTAK, the European Union, and the Ministry of Development. Scientific awards include: Bedri Karafakioğlu Special Award (2000) Siemens Excellence Award (2007) TeknoGirişim Sermaye Desteği Ödülü (2010) He has supervised numerous master’s and PhD students, with theses on topics such as dependency parsing, named entity recognition, and text normalization. He has also served as a consultant for private sector projects in banking, software, and telecommunications, and as a referee for TÜBİTAK, TEYDEB, and the Ministry of Industry and Technology. Dr. Tantuğ leads and participates in active research projects including Turkish text normalization from user-generated content and improving dependency parsing with augmented features. He is a founding member of the ITU Natural Language Processing Group, which continues to be a central hub for NLP research in Turkey.

• Cartography
• Geographic Information Systems
• Geodesy
• +۶ مورد دیگر

Mehmet Ufuk Özerman is a Lecturer in the Department of Geomatics Engineering at the Faculty of Civil Engineering, Istanbul Technical University (ITU). He earned his PhD from ITU’s Department of Geodesy and Photogrammetry Engineering and has been actively contributing to academia since 1986. His institutional affiliation and research activities are centered at ITU's Ayazağa Campus in Istanbul, Turkey. His primary research interests include Cartography , Geographic Information Systems (GIS) , and mathematical methods in geodesy. His work emphasizes computational techniques in surveying, such as joint adjustment of geodetic networks, spherical trigonometry applications in navigation, and efficient matrix storage methods for geodetic computations. These areas reflect a strong integration of theoretical mathematics with practical surveying engineering. The analysis of his publications from the early 1990s reveals a focus on enhancing precision and efficiency in geodetic data processing. His articles address problems in spherical trigonometry, bandwidth optimization in joint network adjustments, and linear storage of band matrices—demonstrating consistent contributions to the mathematical foundations of geomatics engineering. There are no scientific awards mentioned in the provided texts. Mehmet Ufuk Özerman has supervised postgraduate students, including ASLI UNAL and GUZIDE MIRAY PERIHANOGLU, both of whom completed their theses at ITU’s Institute of Science. While no grants or funding sources are explicitly mentioned, his long-standing academic role and student supervision indicate sustained academic mentorship and research activity. No specific laboratories, research teams, or collaborative groups are referenced in the available information.

Serap ÇAKAR KAMANمشاهده پروفایل

استادیار

• Computer vision
• Deep learning
• Object detection
• +۶ مورد دیگر

Serap ÇAKAR KAMAN is an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Computer Engineering. She has maintained a continuous academic career at the university since 2000, progressing from Research Assistant to Lecturer and finally to Assistant Professor. Her educational background includes: Doctorate in Electrical Engineering (2003-2009) from Sakarya University Institute of Science with thesis on "DIGITAL IMAGE WATERMARKING METHODS BASED ON MOMENT-BASED NORMALIZATION" Master's in Computer and Information Engineering (2000-2003) from Sakarya University Institute of Science with thesis on "DETECTING, TRACKING AND TARGET IDENTIFICATION OF OBJECT MOVEMENTS ON VIDEO IMAGES" Bachelor's in Electrical-Electronics Engineering (1996-2000) from Sakarya University Faculty of Engineering Dr. ÇAKAR KAMAN's research spans multiple domains within computer vision and artificial intelligence, with particular expertise in object detection, deep learning applications, and image processing. Her work bridges theoretical computer vision with practical applications in industrial automation, medical imaging, and electric vehicle technology. She has made significant contributions to metal surface defect detection, autonomous charging systems, and facial expression recognition for healthcare applications. Her research demonstrates a consistent pattern of applying advanced computer vision techniques to solve real-world problems across diverse domains. Analysis of her publication trends reveals a clear evolution from foundational work in digital image watermarking to cutting-edge applications of deep learning in industrial settings. Her recent publications (2023-2025) focus on practical implementations in agricultural technology (hazelnut kernel analysis), business intelligence (employee feedback analysis), and marine infrastructure (shore-to-ship charging). The consistent thread through her research is the development of robust computer vision algorithms that enhance automation and precision in various technical contexts. With an H-index of 4 in Web of Science and 114 citations, Dr. ÇAKAR KAMAN maintains an active research profile. Her academic contributions include teaching in the Department of Computer Engineering and likely supervision of graduate students, though specific student information isn't documented in the available materials. Her work contributes significantly to Sakarya University's research profile in computer engineering and supports Turkey's growing expertise in artificial intelligence applications. Her laboratory work appears to focus on computer vision systems with emphasis on real-time processing applications. The research groups she participates in likely include teams working on industrial automation, electric vehicle infrastructure, and medical image analysis, though specific team structures aren't detailed in the available information.

Guiyuan Yangمشاهده پروفایل

مدرس

• Chinese Language and Culture
• English Language Teaching
• Applied Linguistics
• +۳ مورد دیگر

Guiyuan Yang serves as a Lecturer in the Chinese Department at Bogazici University, teaching Chinese language and culture since 2004 after a decade instructing English as a foreign language at Tianjin Normal University in China. Educational background includes a Master of Arts in English Language and Literature from Tianjin Normal University. Research focuses on Chinese Language and Culture, English Language Teaching, and Applied Linguistics, with significant contributions to pedagogical methods for large classrooms, educational technology integration, and literary analysis of American poetry. Their work bridges theoretical frameworks with practical language instruction across cultural contexts. Publications demonstrate an evolution from early 2000s studies on English literature and teaching methodologies toward contemporary Chinese language education, highlighted by the 2020 Turkish translation of Sun Tzu's "The Art of War". Recurring themes include cross-cultural communication, curriculum development for transitional learning stages, and technology-enhanced language acquisition.

• Natural Language Processing
• Computational Linguistics
• Dependency Parsing
• +۳ مورد دیگر

Şaziye Betül Özateş is an Assistant Professor at Boğaziçi University's Institute for Data Science and Artificial Intelligence, specializing in NLP and machine learning. She develops resources and models for Turkish and low-resource languages, including the BOUN Treebank and dependency parsers. Research focuses on dependency parsing for agglutinative languages, computational linguistics, and deep learning applications, with emphasis on Turkish morphology, code-switching parsing, and historical language processing. Recent projects address Ottoman Turkish NLP and calligraphy analysis. Publications demonstrate strong focus on Turkish language resources (40%), parsing algorithms (30%), historical text processing (20%), and code-switching NLP (10%). Recent works show increasing attention to Ottoman Turkish and Arabic script processing, with methods leveraging multilingual BERT and semi-supervised learning. Developed key resources: BOUN Treebank (Turkish syntactic corpus), PUD Treebank (multilingual parallel corpus), BOUN-Pars (LSTM-based Turkish parser), and semi-supervised parsers for code-switched languages. Supervises projects on neural network applications in NLP.

• Natural Language Processing
• Data Science
• Deep Learning
• +۵ مورد دیگر

Savaş Yıldırım is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, College of Engineering. He holds a PhD in Computer Engineering from Trakya University and completed his postdoctoral studies at Eberhard Karls Universität Tübingen, Germany. His academic work is centered on data science and computational linguistics, with a focus on Turkish language technologies. His research interests include Natural Language Processing, Deep Learning, Big Data Analytics, and Open Source software. He actively contributes to advancing Turkish language processing through text normalization, synonym detection, and meronym extraction. His work bridges theoretical NLP with practical applications in public policy and industry. The recent publications of Savaş Yıldırım are primarily in the domain of computational linguistics, with a strong emphasis on Turkish-specific challenges. The articles reflect a consistent trend in unsupervised and knowledge-poor methods for text analysis, focusing on morphological richness and resource scarcity in low-resource languages. Key themes include lexical semantics, text preprocessing, and pattern-based information extraction. Notable scientific contributions include projects funded by TÜBİTAK and EU programs such as: Ağlandırılmış Türk Kamu Alanının Haritalanması (TÜBİTAK 2219) Metin Madenciliği Yöntemlerinin Uygulanması (TÜBİTAK 1001) Akıllı Hazine Nakit Yönetimi (TÜBİTAK TEYDEB) İnsan Kaynakları Süreçlerinde Öngören Mekanizmalar (TÜBİTAK TEYDEB) Engelleri Kaldırarak Bir Araya Gelelim (EU Urban Net – TÜBİTAK 1001) Savaş Yıldırım has served as an academic coordinator and researcher in multiple nationally and internationally funded projects. He has also worked as a Data Science Trainer for The Banks Association of Turkey and as a trainer for IBM’s Academy of Technology. While no formal advisees are listed, his leadership in research projects indicates mentoring and collaborative supervision roles. He maintains an active research blog at openanalitik.wordpress.com . He is associated with research initiatives in data analytics and natural language processing, particularly through project-based labs and interdisciplinary teams focused on public sector data and intelligent systems. These teams often involve collaboration between academia and industry, especially in finance and human resources technology.

İpek Pınar Bekarمشاهده پروفایل

استادیار

• Phonetics
• Phonology
• Computational Linguistics
• +۱۳ مورد دیگر

Assistant Professor İpek Pınar Bekar is a linguist specializing in phonetics and phonology, with a strong focus on both theoretical and applied aspects. Her research spans computational phonetics, speech synthesis, forensic phonology, second language pronunciation, and the phonological structure of Turkish and sign languages. She is actively contributing to academic literature in Türkiye through publications and editorial work. Assistant Professor in Linguistics Specialization in Phonetics and Phonology Editor and contributor to key Turkish academic texts Her research interests include phonological theory, computational modeling of speech, prosody, formant analysis, and the interfaces between phonology and other linguistic domains such as morphology, syntax, semantics, and sociolinguistics. She has also explored applications in mother tongue teaching, second language acquisition, and text-to-speech synthesis. Her work often integrates technical tools like the R programming language for acoustic analysis. The recent publications (2020) demonstrate a strong trend in interdisciplinary phonological research, combining theoretical linguistics with computational methods and practical applications in education and forensics. Her work addresses both Turkish-specific phenomena and universal phonological principles. While no formal scientific awards are mentioned in the text, her editorial role in a comprehensive volume indicates recognition within the academic community in Türkiye. İpek Pınar Bekar has contributed to research advising through her publications and mentorship in academic writing, though no formal students are listed. Her work suggests involvement in advancing phonological research and pedagogy in Turkish academia. She is associated with research in phonological computation, speech technology, and linguistic analysis, likely involving collaboration with other scholars across Turkish universities, though no specific lab or team is named.

• Natural Language Processing
• Computational Linguistics
• Syntactic Analysis
• +۳ مورد دیگر

Şaziye Betül Özateş is an Assistant Professor at the Institute for Data Science and Artificial Intelligence at Boğaziçi University, specializing in Natural Language Processing (NLP) and Machine Learning. She holds a BSc, MSc, and PhD in Computer Engineering from Boğaziçi University, where she was advised by Dr. Arzucan Özgür and Dr. Tunga Güngör. Previously, she was a researcher at the University of Stuttgart’s Institute of Natural Language Processing and a post-doctoral fellow at KUIS AI Center focusing on procedural language learning from natural instructions. Her research interests include natural language processing, computational linguistics, syntactic analysis, and deep learning. She has developed several influential resources, including the BOUN Treebank (9,761 syntactically annotated Turkish sentences), IMST Treebank, and PUD Treebank. Her tools such as BOUN-Pars (a Turkish dependency parser) and the semi-supervised deep dependency parser support morphological and dependency analysis for agglutinative and code-switched languages. Her recent work focuses on historical Turkish NLP, Ottoman Turkish corpus construction, and multilingual BERT-based dependency parsing. She has contributed to code-switching NLP, semi-supervised learning techniques, and sentence similarity kernels for summarization. Her publications span 2016–2025, emphasizing treebanking, parsing optimization, and low-resource language challenges. Key projects include the NakbaTR dataset for Turkish NER, Arabic calligraphy text extraction, and dementia caregiver detection via social media analysis. Her work bridges theoretical linguistics with practical tools, making Turkish NLP resources accessible for global research.

Müjde Güzelkayaمشاهده پروفایل

استاد

• Control Systems
• Fractional Order Control
• Fuzzy Logic Control
• +۷ مورد دیگر

Müjde Güzelkaya is a Professor in the Department of Control and Automation Engineering at Istanbul Technical University (ITU), Faculty of Electrical and Electronic Engineering. She has been a prominent figure in the field of control systems since at least 1983, with over 108 research outputs and an h-index of 30. Her research spans fractional-order control, intelligent systems, and optimization algorithms. She leads multiple active research projects funded by ITU's BAP program and serves as principal investigator on initiatives involving federated learning, robust control, and uncertainty quantification. Her research interests are deeply rooted in control theory and automation , particularly in the design and optimization of controllers using fractional calculus , fuzzy logic , and metaheuristic algorithms like the Big Bang–Big Crunch method. She applies these techniques to diverse domains such as robotics, structural protection, and industrial automation. Her work emphasizes both theoretical development and practical implementation, as seen in applications to quadcopters, building seismic protection, and DC motor control. The most recent articles reflect a strong trend toward integrating fractional calculus with machine learning and distributed intelligence , particularly in system identification and adaptive learning frameworks. Her publications consistently focus on enhancing control performance, robustness, and adaptability in complex, nonlinear systems. Scientific Awards and Recognition: No specific awards are listed in the provided text. Advising and Grants: She is actively mentoring graduate students, with 50 theses currently in progress under her supervision. She has secured multiple competitive research grants, including: Federated Learning-Based System Identification and Uncertainty Quantification (2025–2027) Robust and Adaptive Loss Functions Using Fractional Calculus (2024–2025) Intelligent Systems and Fractional Order Controller Design (2023–2026) Controller Design for Fractional Order Systems (2018–2021) These projects highlight her leadership in cutting-edge control research. Labs and Research Teams: While specific lab names are not mentioned, her role as PI on multiple projects and her extensive collaboration network suggest she leads a research group focused on intelligent control and fractional-order systems at ITU. Her work involves interdisciplinary collaboration across engineering domains.

Recep Firat Cekinelمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Multimodal Fact-Checking
• Explainable AI
• +۷ مورد دیگر

Recep Firat Cekinel is a Turkish NLP researcher who recently obtained his Ph.D. in Computer Engineering from Middle East Technical University (METU). He spent 13 months as a visiting predoctoral researcher at the University of Tübingen and is currently a researcher on the EU-funded EXA4MIND project, where he develops NLP pipelines that convert natural language into database queries using large language models. His research focuses on responsible, scalable AI systems and bridges foundational NLP work with real-world applications. Education: Ph.D. in Computer Engineering, Middle East Technical University (METU), Türkiye Visiting Predoctoral Researcher, University of Tübingen, Germany (13 months) Research Interests: Dr. Cekinel’s work spans natural language processing , multimodal fact-checking , explainable AI , and large language models . He is particularly interested in building responsible and scalable AI systems that integrate foundational research with practical deployments, such as natural-language interfaces for high-performance computing environments. Recent Publication Trends: His 2025 publications reveal a concentrated effort on multilingual and multimodal fact-checking , satire-style debiasing , and NL-to-database-query generation . Earlier work explores graph-based event extraction , Turkish irony detection , and cultural-heritage text mining , demonstrating a trajectory from low-resource Turkish NLP toward globally applicable, responsible-AI systems. Contact & Code: Email: rfcekinel@ceng.metu.edu.tr Office: METU Computer Eng. Dept. A-206, 06800 Ankara, Turkey Phone: +90-(312)-210-5593 GitHub: firatcekinel Google Scholar: profile available