Find Academic Supervisors

• Natural Language Processing
• Computational Linguistics
• Dependency Parsing
• +3 more

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.

Onur VarolView profile

Assistant Professor

• Computational Social Science
• Network Science
• Machine Learning
• +4 more

Onur Varol is an Assistant Professor at Sabanci University's Computer Science Department and leads the VIRAL Lab, which focuses on computational social science, network science, and machine learning. He has affiliations with the Center of Excellence for Data Analytics. His research spans social bot detection, misinformation analysis, and online behavior modeling.

Aykut KoçView profile

Associate Professor

• Machine Learning
• Signal Processing
• Natural Language Processing
• +1 more

Dr. Aykut Koç is an Associate Professor at the Department of Electrical and Electronics Engineering and a faculty member of the National Magnetic Resonance Research Center (UMRAM) at Bilkent University, Turkey. He leads the AykutKoc Lab, focusing on interdisciplinary research at the intersection of machine learning, signal processing, natural language processing, and graph signal processing. Education: B.S. in Electrical and Electronics Engineering (2005, Bilkent University); M.S. in Electrical Engineering (2007), M.S. in Management Science and Engineering (2009), and Ph.D. in Electrical Engineering (2011) under Professor Lambertus Hesselink at Stanford University; LL.B. in Law (Ankara University). His research integrates mathematical signal processing techniques (e.g., fractional Fourier and linear canonical transforms) with modern machine learning architectures like transformers and graph neural networks. Recent work explores semantic communication systems, bias mitigation in legal language models, and cross-modal applications in biomedical imaging and radar technology. Dr. Koç has published extensively in IEEE and Springer journals, with recent articles analyzing Fourier-enhanced transformers, graph-based NLP methods, and time-vertex signal analysis. His work addresses both theoretical innovations and practical applications, including schizophrenia diagnosis, legal outcome prediction, and maritime surveillance. Scientific Awards: Science Academy Young Scientists Award (BAGEP), 2023. He has supervised numerous graduate and undergraduate researchers, many of whom have transitioned to top-tier institutions such as MIT, UCLA, and TU Darmstadt. Dr. Koç actively serves as Associate Editor for multiple IEEE journals and participates in conference program committees, including EMNLP's Natural Legal Language Processing (NLLP) workshop.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +7 more

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.

• Information Retrieval
• Natural Language Processing
• Turkish Language Processing
• +4 more

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).

Engin ErzinView profile

Professor

• Artificial Intelligence
• Multimedia Systems
• Computer Vision
• +6 more

Engin Erzin is a Professor at Koç University's College of Engineering, leading the KUIS AI Lab and Multimedia, Vision and Graphics Lab . His research focuses on AI-driven human-centric systems, affective computing, and multimodal interaction analysis. He has contributed extensively to robotics, speech processing, and human-robot interaction through over 70 peer-reviewed publications since 2008. Research interests include: Affective computing and emotion recognition from speech/gestures Human-robot interaction and socially engaging agents Speech-driven animation and gesture synthesis Multimodal data fusion for interaction analysis Deep learning applications in robotics and biomedical engineering Recent work emphasizes: Developing adaptive pHRI controllers for manufacturing tasks Creating engagement measurement frameworks for human-machine interfaces Advancing Turkish speech recognition through self-supervised learning Designing multimodal databases for interaction studies Labs: KUIS AI Lab : Focuses on AI applications in robotics and human-computer interaction Multimedia Lab : Specializes in vision, graphics, and audiovisual analysis

• Data Mining
• Privacy-Preserving Computation
• Artificial Intelligence
• +3 more

Onur KARDEŞ serves as Assistant Professor in the Department of Computer Engineering at Beykent University's Faculty of Engineering and Architecture since 2020. His prior academic appointments include: Research Assistant, Department of Computer Science, Stevens Institute of Technology (2004-2008) Lecturer, Department of Mathematics and Computer Science, Faculty of Arts and Sciences, Beykent University (2000-2004) His research integrates data mining, privacy-preserving computation, and artificial intelligence with practical applications in educational technology and urban systems. Key contributions include developing privacy-enhancing protocols for distributed data mining and pioneering generative AI solutions for automated student assessment and digital teaching assistants. Analysis of his 2023-2025 publications reveals accelerating focus on generative AI implementations, particularly in educational evaluation (automated examination paper analysis) and urban planning (AI-driven smart city frameworks). This evolution demonstrates strategic adaptation to emerging technologies while maintaining core expertise in secure computation and data mining.

• Natural Language Processing
• Text Normalization
• Named Entity Recognition
• +5 more

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
• Natural Language Processing
• Computational Linguistics
• +6 more

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.

Mustafa SertView profile

Associate Professor

• Audio Signal Processing
• Machine Learning
• Semantic Multimedia
• +5 more

Mustafa Sert , currently serving as Associate Professor at Başkent University's Department of Computer Engineering and as Vice Dean of the Faculty of Engineering, has made significant contributions to audio signal processing, machine learning, and semantic multimedia. He earned his PhD (2006), MSc (2001), and BSc (1997) in Computer Engineering from Gazi University, supervised by prominent academics. PhD: Gazi University (2006) MSc: Gazi University (2001) BSc: Gazi University (1997) His research focuses on audio-visual content analysis , multimodal information fusion , and machine learning applications in semantic multimedia systems. He leads projects at the intersection of deep learning , speech processing , and acoustic pattern recognition , with work appearing in venues like IEEE Access, ACM Multimedia conferences, and Signal Processing and Communications Applications Conference (SIU). Recent publications demonstrate trends in automated audio captioning , medical speech analysis , and educational data mining , with applications spanning mental health detection, chatbot development, and reviewer selection systems. His work integrates transformer architectures , convolutional networks , and fuzzy decision-making models . Scientific Recognitions: Best Paper Award (7th Eurasian Congress on Emergency Medicine 2021) Outstanding Reviewer Awards (IEEE ICME 2020, 2021) Outstanding Area Chair Award (ACM Multimedia 2024) Academic Leadership includes roles as Senior IEEE Member, technical committee board positions in IEEE CTSoc divisions, and ACM membership. He supervises over 20 graduate students in topics ranging from depression detection through speech to geothermal permeability estimation , while maintaining active involvement in conference organization and journal reviewing for top-tier publications.

Serdar ARSLANView profile

Lecturer

• Database Management Systems
• Data Structures and Algorithms
• Machine Learning
• +3 more

Dr. Serdar Arslan is a Lecturer at the Department of Computer Engineering at Cankaya University. He holds a PhD in Computer Engineering from Middle East Technical University (METU), with a thesis on multidimensional data indexing. His academic background includes a Master's (2005) and Bachelor's (2001) in Computer Engineering from METU and Hacettepe University, respectively. His research focuses on database systems, machine learning, multimedia data indexing, and forecasting models. Education: Bachelor of Engineering, Computer Engineering, Hacettepe University (2001) Master of Science, Computer Engineering, METU (2005) Doctor of Philosophy, Computer Engineering, METU (2018) Research Interests: Machine Learning applications in healthcare forecasting and financial markets Advanced indexing techniques for multimedia databases (e.g., MM-FOOD structure) Natural language processing for stance detection in political discourse Hybrid forecasting models combining LSTM and Prophet algorithms Domain-specific NLP for product name extraction in Turkish text Publications: His recent work emphasizes machine learning-driven solutions for complex systems, including pandemic modeling, cryptocurrency analysis, and conflict discourse analysis. His earlier contributions focused on multimedia indexing and image retrieval systems using MPEG-7 standards. The 2025 paper on OSINT architecture frameworks highlights his expanding focus on cybersecurity and system design. Labs/Teams: While no specific lab is mentioned, his GitHub repositories (e.g., Forecasting, NLP projects) suggest active involvement in collaborative research projects related to his domains.

Gültekin IşıkView profile

Associate Professor

• Deep Learning
• Machine Learning
• Computer Vision
• +4 more

Assoc. Prof. Gültekin Işık is affiliated with the Department of Computer Hardware at Iğdır University's Faculty of Engineering. He holds a PhD in Computer Engineering from Hacettepe University (2011–2019), focusing on Turkish dialect recognition using deep learning. His academic roles include serving as Head of the Department from 2019 to 2021. His research interests span deep learning applications in computer vision (e.g., YOLO-based crowd detection), optimization algorithms (e.g., Slime Mould Algorithm), environmental modeling (solar power efficiency prediction), and healthcare (breast cancer detection). He has authored numerous peer-reviewed articles and books, including works on convolutional neural networks for plant disease identification and hybrid optimization techniques for data clustering. Prof. Işık teaches advanced courses such as İleri Derin Öğrenme (Advanced Deep Learning) and Sinir Ağları (Neural Networks). His recent work emphasizes real-time video analysis for public health (social distancing) and energy systems optimization. Despite no listed awards, his contributions to interdisciplinary fields like bioacoustics and renewable energy are notable. He has advised two master’s students: Mehmet Şirin Gündüz (2023) on YOLO-based crowd detection and Seda Bayat (2021) on bird species recognition using deep learning. His research integrates theoretical models with practical applications in domains ranging from agriculture to medical imaging.

İBRAHİM RIZA HALLAÇView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Parallel and Distributed Systems
• +3 more

İbrahim Rıza Hallaç is an Assistant Professor at RAFET KAYIŞ FACULTY OF ENGINEERING, Department of Computer Engineering. He holds a PhD (2021), Master's (2014), and Bachelor's (2011) in Computer Engineering from Firat University, with doctoral research on social media analysis using deep learning methods under advisor Galip Aydın. His research focuses on: Artificial Intelligence and language models Machine learning for distributed systems Big data analytics and cloud computing Natural language processing applications Social media sentiment analysis Radar-based object detection systems His publications (2015-2024) demonstrate consistent focus on machine learning applications across diverse domains including social network analysis, distributed computing, Turkish NLP, and sensor data processing. Recent works emphasize radar-based multi-target detection (2024), credit scoring models (2023), and wind speed estimation (2023), reflecting expertise in scaling AI solutions for real-world problems. He has led four national R&D projects: Deep Learning-Based Face Recognition Authorization System (2017-2019) DEĞİRMEN Big Data Analysis Platform for Turkish Armed Forces (2017-2021) KOSGEB Innovation Program for Face Recognition Systems (2017-2019) Cloud-Based Social Media Reputation Analysis System (2015-2017) No students, awards, or contact emails are documented in available records.

• Computer Engineering
• Artificial Intelligence
• Software Engineering
• +2 more

Gizem Gümüşçekiçci is a Research Assistant at Işık University , affiliated with the Faculty of Engineering and Natural Sciences in the Department of Computer Engineering . Her work focuses on Artificial Intelligence , Software Engineering , and Computer Networks . Education : Master's in Computer Engineering (Full Scholarship, ongoing since 2021), Bachelor's in Computer Engineering (75% Scholarship, 2016-2021) Her research integrates Natural Language Processing and Deep Learning , covering areas like Turkish Embedding Models , Sarcasm Detection , and Sign Language Accessibility . Recent publications highlight applications in sentiment analysis, diffusion models, and social network security. No scientific awards are explicitly mentioned in the provided texts.

• Geographic Information Systems (GIS)
• Remote Sensing
• Photogrammetry
• +5 more

Dr. Gülsüm Çiğdem Çavdaroğlu Akkoç is a full-time Assistant Professor in the Information Technologies Department at Işık University's Faculty of Economics, Administrative and Social Sciences. She holds a multidisciplinary background with degrees in Mathematics Engineering, Geomatics Engineering, and Turkish Language & Literature. Education Ph.D. in Photogrammetry Engineering – Yıldız Technical University (2006–2013) M.S. in Photogrammetry Engineering – Yıldız Technical University (2003–2006) B.S. in Mathematics Engineering – Yıldız Technical University (1998–2003) B.A. in Turkish Language & Literature – Anadolu University (2016–2020) Research Interests Dr. Akkoç's research spans remote sensing , GIS , and machine learning , with applications in environmental monitoring, urban mobility, and health informatics. Her work leverages satellite imagery, mobile data, and AI to address challenges such as wildfire detection, air pollution tracking, and disease diagnosis. She actively integrates spatial data with AI to support smart city development and sustainable resource management. Scientific Awards First Prize – Mobilya Ar-Ge Proje Pazarı (2013), Entrepreneurship Category Supervision & Projects She has supervised four master's theses and led several EU and national projects including: BEE-OPTECH4Honey : Optimizing beekeeping routes using ICT TOP4HoneyChain : A sustainable smart honey value chain platform Open Data Platform for Precision Agriculture Labs & Teams Dr. Akkoç collaborates with interdisciplinary research teams in the fields of AI, geospatial technologies, and agricultural informatics. Her lab activities include developing machine learning models for real-world applications in health, environment, and urban systems.