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Ceyhun Burak Akgül is a Part-Time Lecturer specializing in Computer Vision, Machine Learning, and Statistical Data Analysis. His research focuses on interdisciplinary applications of visual data processing, including medical imaging and 3D object recognition. He maintains a personal website at cba-research.com and can be contacted at cb.akgul@gmail.com . His work spans topics such as image captioning, visual dictionaries, and symbolic feature detection. Key contributions include developing algorithms for action recognition using depth cameras and frameworks for leaf and object recognition. His research also integrates medical applications, such as analyzing Alzheimer’s patient movements and automated diagnosis using imaging data. Akgül’s publications frequently address challenges in 3D shape descriptors, feature selection, and interdisciplinary methodologies. His recent work includes exploring visual dictionaries and improving image processing techniques through model-driven approaches. His academic contributions are evident in journals like the Journal of Visual Communication and Image Representation, and he has participated in competitions like SHREC. Despite his extensive publication record, no formal awards or grants are explicitly mentioned in the provided data.

• Computer vision
• Machine learning
• Statistical data analysis
• +3 more

Beyza Eken serves as Assistant Professor in the Department of Software Engineering at Sakarya University's Faculty of Computer and Information Sciences, teaching core courses including Software Project Management, Natural Language Processing, and Graduation Projects while maintaining active research in software engineering and AI applications. Her academic credentials include: Doctorate in Computer Engineering from Istanbul Technical University (2015), thesis: "Software Defect Prediction" Master's in Computer Engineering from Istanbul Technical University (2011-2015), thesis: "Entity Name Recognition in Short Texts" Bachelor's in Computer Engineering from Sakarya University (2007-2011) Dr. Eken's research integrates machine learning with software engineering, specializing in defect prediction models that incorporate personalized developer factors and industrial deployment challenges. Her work bridges natural language processing for Turkish social media analysis with software quality assurance, demonstrating expertise in both theoretical modeling and practical implementation in industrial settings. Recent expansions include neuro-symbolic AI for test oracle generation and MLOps frameworks. Publication trends reveal consistent focus on empirical software engineering from 2018-2021 (defect prediction, community smells, industrial deployment), evolving into cutting-edge domains by 2023-2025 (neuro-symbolic testing, employee feedback analysis, MLOps). Her work shows strong industry-academia collaboration patterns with increasing methodological sophistication. Dr. Eken actively contributes to academic service as reviewer for ACM Transactions on Software Engineering and Methodology (2024) and IEEE Transactions on Software Engineering (2023). She leads research projects including "Developer-specific error prediction modeling" (2020) and the Mevlana exchange project with Ryerson University on data mining for defect prediction (2018), while supervising graduation projects and research area courses that develop student expertise in software engineering practices. Her international research engagement includes participation in the ASTERIx project at Università della Svizzera Italiana's Software Testing and Analysis Research Group (2023), demonstrating ongoing commitment to global collaboration in software engineering advancements.

• Software Defect Prediction
• Natural Language Processing
• Machine Learning in Software Engineering
• +2 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.

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

• Artificial Intelligence
• Natural Language Processing
• Computational Linguistics
• +6 more

Oğuz Haşlakoğlu is an Associate Professor in the Department of Architecture at Istanbul Technical University . His research spans interdisciplinary art, aesthetics, visual design, and art philosophy, with a focus on the intersection of classical thought and modern artistic practices. His scholarly work explores themes such as the role of museums in canon formation, new materialism, design ethics, and the ontological processes of art creation. He has led projects like Sanat ve Kültür and Revolving Fund Romantizmin 20 Yüzyıl Avangart Sanatına Etkileri , reflecting his engagement with both theoretical and applied research. Education : MFA in Painting from Mimar Sinan Fine Arts University (2004–2005), MA in Philosophy (1995–1999), MA in Painting (1991–1994), and BFA in Painting (1986–1991). Administrative Roles : Department Head at Istanbul Technical University (2016), Dean at Istanbul Aydın University (2011–2012), and leadership roles in committees at Akdeniz University and UNESCO AIAP Turkey National Committee. His academic contributions include membership in institutions like the I.T.U. Bilim-Toplum Application-Research Center and the Yapay Zekâ ve Veri Bilimi Uygulama ve Araştırma Merkezi . His email is haslakoglu@itu.edu.tr .

• Fine Arts
• Interdisciplinary Art
• Art Philosophy
• +5 more

Seda Keskin Avcı serves as Professor in the Chemical and Biological Engineering Department at Koç University, Istanbul, directing the Nanomaterials, Energy, and Molecular Modeling Research Group (NEMO). Appointed in 2010 and promoted to full professor in 2018, she holds the distinction of being Türkiye's youngest female professor in chemical engineering. Her research bridges computational modeling with experimental validation to develop advanced materials for sustainable energy solutions. Education: PhD, Georgia Institute of Technology (2009) MSc, Boğaziçi University (2006) BS, Boğaziçi University (2004) Professor Keskin's research focuses on AI-accelerated design of metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) for gas separation and carbon capture. She pioneers integration of molecular simulations with machine learning to predict material properties, specializing in ionic liquid composites and flexible frameworks. Her work targets critical energy challenges including CO 2 /N 2 separation, hydrogen purification, and acetylene/ethylene processing through computational-guided material discovery. Analysis of her 2024-2025 publications reveals a decisive shift toward artificial intelligence integration in materials science, with 80% of recent work combining machine learning with molecular simulations. Key themes include high-throughput screening of MOF/COF databases, development of IL-MOF composites for enhanced selectivity, and exploration of framework flexibility effects. This interdisciplinary approach has established new methodologies for accelerating materials discovery cycles in porous media research. Scientific Awards: ERC Starting Grant (2017) ERC Consolidator Grant (2023) Outstanding Women in Chemical Engineering by Chemical Engineering Research and Design TÜBİTAK Incentive Award (2013) TÜBA Gebip Award (2012) Professor Keskin leads the NEMO research group with significant funding including two landmark ERC grants - Türkiye's first for a female engineer in this field. Her group operates at the intersection of computational chemistry and chemical engineering, developing open-source simulation frameworks while maintaining strong industry partnerships for membrane technology commercialization. Current projects focus on scaling AI-designed materials for industrial carbon capture applications. The Nanomaterials, Energy, and Molecular Modeling Research Group (NEMO) operates advanced computational infrastructure for molecular dynamics simulations and machine learning training. The group maintains collaborative ties with Georgia Tech, MIT, and European research consortia while actively developing experimental validation capabilities for computationally predicted materials through Koç University's nanotechnology center.

• Material Science
• Energy
• Artificial intelligence-guided material design and discovery
• +2 more

Ali İbrahim Can GÖZÜM serves as an Associate Professor in the Department of Preschool Education at Kafkas University's Dede Korkut Faculty of Education. With dual doctoral degrees in Preschool Education from Gazi University and Science Education from Ondokuz Mayıs University, he specializes in early childhood science and technology education. His academic journey includes progressive appointments from Research Assistant (2013) to Associate Professor (2022), alongside administrative roles including Dean Assistant and Career Center Director. His research focuses on early childhood STEM education , digital game mediation , and cognitive development , reflected in over 90 publications with significant international impact (Google Scholar h-index: 18). Current projects examine flipped classroom models in language education and nature-based learning environments. His editorial leadership includes Editor-in-Chief of e-Kafkas Journal of Educational Research and Associate Editor for Frontiers in Education 's STEM section. Notable scientific recognition includes TUBITAK's Publication Incentive Award. His advising includes master's theses on self-regulation and number sense development. Active in professional development, he conducts workshops on digital parenting and AI libraries, demonstrating commitment to bridging research with practical educational applications.

• Early Childhood Education
• STEM Education
• Science and Technology Education
• +3 more

Prof. Emine Yılmaz is a faculty member in the Department of Computer Science at University College London (UCL) and leads the UCL Web Intelligence Group. She is also affiliated with the UCL Artificial Intelligence Center. Her research focuses on designing systems for contextual task completion assistance, task-based knowledge graphs (e.g., Wikihow integration), task-focused dialogues, and the application of Large Language Models (LLMs) to control task-specific agents. She has presented her work at events such as the Sabancı University Dean’s Speaker Series, emphasizing innovations in intelligent assistants and search engines.

• Artificial Intelligence
• Knowledge Graphs
• Natural Language Processing
• +3 more

Dr. Serkan Düzgün is an Associate Professor at Gazi University's Faculty of Education, Department of Basic Education, specializing in Classroom Education. He has previously worked as a part-time lecturer at Ankara Hacı Bayram Veli University and Ankara Yıldırım Beyazıt University. PhD, Master's, and Bachelor's degrees from Gazi University Active in instructional technologies, AI in education, STEM, and neuroscience applications Key contributor to Turkey's national education projects and civil society initiatives His research focuses on the integration of artificial intelligence in pedagogical practices, robotic coding platforms for K-12 education, and the cognitive impacts of neuroscience-based teaching methods . Recent work examines distance education challenges during the pandemic, learning style adaptations, and self-regulated learning in virtual environments. Current publications emphasize AI-driven educational tools , technology-enhanced literacy instruction , and virtual classroom dynamics . His 15 most recent articles (2021-2024) span topics like robotic coding in STEM education, emotional intelligence in remote teaching, and AI applications in qualitative research. Dr. Düzgün has conducted 108 projects, advised 3 theses, and actively participates in open-access initiatives and UN Sustainable Development Goals implementation through educational technology. He also played a pivotal role in establishing the "Voice of Turkish" Radio at Yunus Emre Institute.

• Instructional Technologies
• Artificial Intelligence in Education
• STEM Education
• +3 more

Anil Kuş is a Lecturer at Yozgat Bozok University's Boğazlıyan Vocational School, specializing in applied AI research and teaching. He holds a Ph.D. candidacy at Mersin University and has 10 years of experience in software engineering, focusing on Web/Mobile development and AI applications. Education: Ph.D. Candidate, Mersin University (ongoing) Research Interests: Bridging academic research with real-world applications, particularly in Large Language Models (LLMs), Explainable AI (XAI), Generative AI, Vision-Language Models (VLMs), and Human-Robot Interaction. Active in developing deep learning models using Python, PyTorch, TensorFlow, and NLP libraries like Transformers and spaCy. Projects & Innovation: Led interdisciplinary R&D projects at Toros University's Smartlab Technology Center, resulting in patents and utility models. Research presented at conferences and applied in innovation-oriented projects. Labs/Teams: Formerly part of the Smartlab Technology Center, focusing on AI-driven software development and R&D collaboration.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +8 more

Hulya Yalcin is an Assistant Professor in the Department of Mechanical Engineering at Istanbul Technical University. Her research focuses on artificial intelligence applications in robotics, computer vision, and precision agriculture. She leads projects in musculoskeletal modeling, plant phenology monitoring, and assistive technologies for elderly care. Her work contributes to UN Sustainable Development Goals related to innovation, health, and sustainable agriculture. Key projects include using deep learning for crop yield estimation and developing exergaming systems to improve elderly health. She has authored 52 research outputs and secured funding for initiatives like AISENSE (EU-funded exergames) and plant classification via computer vision. Publications span robotics control, medical engineering, and agricultural informatics. Notable contributions include knee orthosis gait learning via deep reinforcement learning and low-resource Turkish speech recognition improvements. As Principal Investigator, she manages projects on plant classification using CNNs, drone-based depth mapping, and multimodal assisted living systems. Her research bridges AI with practical applications in healthcare, agriculture, and robotics.

• Artificial Intelligence
• Robotics
• Computer Vision
• +4 more

Assoc. Prof. ÖNDER BİLGİN is a prominent academic at Akdeniz University , where he has served in the Faculty of Letters, Department of History and Philosophy since 2010, advancing from Assistant Professor to Associate Professor in 2020. His scholarly leadership includes multiple tenures as Head and Deputy Head of Department, Board Member roles, and coordination of international exchange programs. Education: Ph.D. in History of Philosophy (Ankara University, 2001-2008), MA in Philosophy (Fırat University, 1997-2001), BA in Theology (Erciyes University, 1990-1997). His research spans Ethics , Social Sciences , and History of Philosophy , with a focus on Islamic ethics (e.g., Al-Ghazali), classical traditions (Aristotle, Heraclitus), and contemporary issues like neoliberal subjectivity. Articles published in journals such as Turkish Academic Research Review and Uluslararası Sosyal Araştırmalar Dergisi reflect his interdisciplinary engagement. Scientific activity includes 34 publications, 12 thesis advisories, and participation in peer-review processes for journals like Toplum Bilimleri Dergisi . He serves on boards including the Uluslararası Türk Kültür Coğrafyasında Eğitim Bilimleri Araştırmaları Derneği and Türk Felsefe Derneği , and has organized international symposia such as the International Antalya Nomadic and Turkishness Studies and Art Symposium (2022).

• Ethics
• Social Sciences
• Philosophy
• +3 more

Assoc. Prof. Dr. Yüksel Yurtay is an active faculty member at Sakarya University's Faculty of Computer and Information Sciences, Department of Data Science and Analytics. With a career spanning over three decades at the university since 1993, he has established himself as a prominent researcher and educator in the fields of data science, artificial intelligence, and business analytics. Education: Doctorate (2011-2020): Sakarya University, Institute of Business Administration/Production Management and Marketing, Thesis: "An empirical study on the impact of the dashboard on decision processes in the context of supply chain management" Master's (1996-1998): Sakarya University, Institute of Social Sciences/Production Management and Marketing, Thesis: "Activity based costing system and an application in electro-mechanical industry" Bachelor's (1987-1991): Anadolu University, Faculty of Arts and Sciences/Mathematics Dr. Yurtay's research focuses on the intersection of data science and business applications, with particular emphasis on dashboard systems, key performance indicators, and supply chain management. His work bridges theoretical computer science with practical business applications, developing innovative solutions for performance monitoring, decision support, and process optimization. His research portfolio demonstrates consistent productivity with publications spanning from 2018 through 2025, showing no signs of slowing down. Analysis of Dr. Yurtay's recent publications (2018-2025) reveals several key research trajectories: a strong focus on dashboard and KPI systems for business decision-making, growing interest in AI applications for emotion recognition (particularly in call center contexts), development of novel metaheuristic algorithms for optimization problems, and application of computer vision techniques for specialized detection tasks. His work consistently combines theoretical algorithm development with practical business applications. Dr. Yurtay has successfully secured research funding from prestigious sources including TÜBİTAK (project 1505) and industry partnerships with companies like Turkcell Global Bilgi. His current projects focus on real-time emotion recognition using deep learning and business process optimization. As an educator, Dr. Yurtay teaches core courses in numerical analysis, software engineering, computer engineering design, and data science. He has supervised graduate theses, including Akın YAŞAR's work on real estate photo quality evaluation using deep learning. His teaching portfolio reflects his expertise across both theoretical computer science and applied data analytics.

• Artificial Intelligence
• Machine Learning
• Data Science
• +8 more

Mehmet Çiçek is a Professor at Gaziantep University's Faculty of Education in the Department of Turkish Language Education. He holds a doctorate in Linguistics from Université de Reims Champagne-Ardenne (France) and has served in various academic and administrative roles since 1992. Doctorate: Linguistics, Université de Reims Champagne-Ardenne (1995-1999) Master's: Linguistics, Université de Reims Champagne-Ardenne (1993-1995) Licence: Atatürk University, Turkey (1987-1991) His research focuses on Turkish language education, semiotics, discourse analysis, and cross-linguistic studies. Recent work examines textual analysis, cultural representation in language learning, and pedagogical methodologies. His publications span Turkish language structure, semiotic systems, and educational applications. Articles include analyses of adjective placement, plural/possessive morphology, and discourse in literary and visual contexts. Prof. Çiçek has supervised multiple graduate theses on Turkish pedagogy, cultural transfer in language teaching, and discourse analysis. He has held leadership roles including Faculty Dean and Department Chair at Gaziantep University. He contributes to academic governance as a board member and serves on examination juries for professorship and doctoral applications.

• Turkish Language Education
• Linguistics
• Semiotics
• +4 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.

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