جستجوی استاد راهنمای دانشگاهی

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.

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

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.

• Machine Learning
• Signal Processing
• Natural Language Processing
• +۱ 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.

• Information Security and Reliability
• Cyber Security
• Artificial Intelligence
• +۱۳ 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.

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

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
• +۳ مورد دیگر

Emre Ugur is an Associate Professor in the Department of Computer Engineering at Bogazici University, where he serves as the head of the Cognition, Learning and Robotics (CoLoRs) laboratory. His research focuses on bridging the gap between continuous sensorimotor experiences and discrete symbolic representations in robotics. Funded by major international sources including the European Commission's Horizon 2020 program and TUBITAK, his work has significant implications for cognitive robotics and autonomous systems. Education: PhD in Computer Engineering from Middle East Technical University (METU, Turkey) Ugur's research interests center on cognitive and developmental approaches to robotics, with particular emphasis on neuro-symbolic integration, affordance learning, and symbol emergence. His work explores how robots can autonomously develop high-level cognitive capabilities through continuous interaction with their environment, similar to human cognitive development. His approach combines machine learning, cognitive science, and robotics to create systems that can learn, predict, and reason about their actions. His recent publications reveal a strong trajectory toward neuro-symbolic robotics, where he develops methods for extracting discrete symbolic representations from continuous sensorimotor experiences. This work enables robots to perform complex planning and reasoning tasks while maintaining connection to physical reality. There is also significant focus on social robotics, particularly in human-robot interaction, social navigation, and embodied cognition. Scientific Awards: The Young Scientist Award by the Science Academy (BAGEP) The Excellence in Teaching Award by the Faculty of Engineering (2023) As Principal Investigator of major projects including INVERSE (EU Horizon 2025), DEEPPLAN (TUBITAK), and previously DEEPSYM and IMAGINE, Ugur has established a robust research program that bridges theoretical advances with practical applications. He has supervised numerous PhD and Master's students who have made significant contributions to the field. His leadership extends to organizing major workshops at top robotics conferences including IROS, RSS, and ICRA. At the Cognition, Learning and Robotics (CoLoRs) lab, Ugur leads research on cognitive robotics, developmental robotics, and neuro-symbolic AI. The lab explores fundamental questions about how robots can develop understanding of their actions, learn from interaction, and form abstract representations necessary for high-level cognition. Current projects focus on symbolic reasoning, prediction, and planning in robotic systems.

• Robotics
• Robot Learning
• Cognitive Robotics
• +۵ مورد دیگر

Selma Tekir is an Associate Professor in the Computer Engineering Department at Izmir Institute of Technology. She completed her undergraduate studies in Computer Engineering at Ege University in 2001, followed by a master's degree from Izmir Institute of Technology in 2004, and earned her PhD from Ege University in 2010. In 2009, she worked as a visiting researcher at the University of Konstanz, Germany. Her educational background includes: B.Sc.: Computer Engineering, Ege University (2001) M.Sc.: Computer Engineering, Izmir Institute of Technology (2004) Ph.D.: Computer Engineering, Ege University (2010) Dr. Tekir's research spans multiple areas of natural language processing and computational linguistics, with a particular focus on Turkish language processing. Her work explores text mining, news analysis, information warfare, and the application of deep learning techniques to linguistic problems. She has made significant contributions to counterfactual detection in Turkish, multi-modal language models, and the integration of symbolic reasoning with neural approaches. Her research often bridges theoretical advances with practical applications, particularly in the Turkish language context which presents unique challenges as a morphologically rich agglutinative language. Analysis of her recent publications reveals a strong trend toward advancing natural language understanding systems for Turkish, developing methods for counterfactual detection, enhancing question answering systems with knowledge graphs, and applying graph neural networks to biological sequence analysis. Her work demonstrates growing interest in combining symbolic reasoning with neural approaches and exploring self-reflection capabilities in language agents. Dr. Tekir has received research funding for projects including: Consistency and Reliability Assessment in News Chains (TÜBİTAK ARDEB 3501) Application of Data Analysis and Visualization Techniques on Historical Sources (BAP) She teaches courses including CENG 381 - Stochastic Processes, CENG 613 - Scientific Research Methods in Computer Science, and SEDS 501 - Introduction to Data Science.

• Natural Language Processing
• Text Mining
• Machine Learning
• +۵ مورد دیگر

F. Yeşim İKİKAT serves as a Researcher at the Department of Computer Engineering within the Faculty of Engineering at Turkish-German University, a position held since 2022. Her academic foundation spans computational engineering with interdisciplinary applications in security systems and semantic analysis. Her educational qualifications include: Doctorate in Computer Engineering from Istanbul Technical University Institute of Graduate Education (2019) Master's in Computer Engineering from Yildiz Technical University Institute of Science (2014-2019, with thesis) Bachelor's in Computer Engineering from Atilim University Faculty of Engineering (2007-2012) Research interests center on Artificial Intelligence, Algorithms and Computational Theory, and Information Security and Cryptology, with specialized work in Parallel Algorithms, Natural Language Processing, and Image Encryption. Her methodology combines computational modeling with cryptographic techniques to solve complex engineering and information system challenges, particularly in high-performance computing environments and secure data transformation. Publication trends reveal evolving expertise from computational mechanics (2012 thermoelasticity simulations) to security applications (2018 image encryption) and semantic analysis (2015 Wikipedia linking). This progression demonstrates consistent application of algorithmic innovation across engineering simulations, multimedia security, and knowledge representation domains. No scientific awards were documented in the source material. Advising activities and research grants are not referenced in the available information. Laboratory affiliations or research team memberships were not specified in the provided text.

• Computer Science
• Artificial Intelligence
• Algorithms
• +۴ مورد دیگر

Can Özturan is a Professor in the Department of Computer Engineering at Bogazici University in Istanbul, Turkey. He joined the department as a faculty member in 1996 after completing his Ph.D. in Computer Science from Rensselaer Polytechnic Institute in 1995 and working as a Postdoctoral Staff Scientist at the ICASE (Institute for Computer Applications in Science), NASA Langley Research Center. His research interests span Blockchain Technologies, Parallel Processing, High Performance Computing, Graph Algorithms, Scientific Computing, Resource Management, and Grid/Cloud Computing. Over his career, his research focus has evolved from parallel processing and graph algorithms toward blockchain technologies, particularly focusing on privacy-preserving techniques, fraud detection, and performance optimization in Ethereum systems. An analysis of his recent publications (2021-2025) reveals a strong concentration on blockchain applications, with particular emphasis on privacy-preserving protocols using zero-knowledge proofs, fraud detection in transaction graphs, and performance optimization for blockchain systems. His work bridges theoretical computer science with practical blockchain implementations, often applying parallel processing techniques to blockchain challenges. Professor Özturan teaches courses in Blockchain Programming (CMPE483), Parallel Processing (CMPE478), Systems Programming (CMPE230), Graph Algorithms (CMPE528), and Compiler Design (CMPE425), demonstrating his expertise across both foundational and emerging areas of computer engineering.

• Blockchain Technologies
• Parallel Processing
• High Performance Computing
• +۴ مورد دیگر

Belgin Ergenç Bostanoğlu is an Associate Professor in the Computer Engineering Department at Izmir Institute of Technology (Turkey). Her research focuses on query optimization in distributed databases, association rule mining, privacy-preserving data mining, and graph-based algorithms. She leads the Dworld research laboratory and has held academic and industry roles since the 1980s. Education: B.Sc. in Computer Engineering, Middle East Technical University (1983) M.Sc. in Computer Engineering, Izmir Institute of Technology (2002) Ph.D. in Computer Engineering, Paul Sabatier University, France (2008) Research Interests: Dynamic frequent itemset mining and hiding under multiple support thresholds Subgraph mining in evolving graphs Federated query processing over linked data Privacy-preserving techniques in distributed databases Medical NLP applications (e.g., TurkMedNLI dataset) Her recent work emphasizes large-scale graph analysis, medical NLP dataset development, and adaptive join operators for federated SPARQL queries. She has contributed to over 30 peer-reviewed publications and led projects like the TÜBİTAK ARDEB 3501 platform for dynamic frequent itemset mining. Teaching: Courses include Advanced Database Management Systems, Knowledge Discovery, and Privacy-Preserving Data Mining. Labs & Projects: Manages Dworld lab and coordinates projects such as 'Turkish Medical NLP Model Development' (BAP-funded) and the Behavioral Next Generation Wireless Networks COST Action.

• Database Systems
• Data Mining
• Privacy-Preserving Techniques
• +۳ مورد دیگر

Shahram TAHERI is an Assistant Professor in the Department of Computer Engineering at Antalya Bilim University (ABU), Turkey, since 2019. Previously, he served as a faculty member at Azad University, Iran, for 8 years. He holds a Ph.D. in Computer Engineering from Eastern Mediterranean University, a Master’s from Shiraz University, and a Bachelor’s from Shahid Bahonar University of Kerman. Research Interests: Biomedical Image Processing Signal Processing Deep Learning Pattern Recognition Neural Networks Key Trends in Publications: His work focuses on applying deep learning and neural networks to biomedical image and signal processing, particularly in age estimation, cancer histopathology, and animal classification. His research spans both multi-stage feature fusion and magnification-specific analysis.

• Biomedical Image
• Signal Processing
• Deep Learning
• +۲ مورد دیگر

Dr. Didem Unat is an Associate Professor at Koç University, College of Engineering, Department of Computer Engineering . Her research focuses on High Performance Computing (HPC) , GPU Computing , and Compiler Design , with particular emphasis on data locality optimization, multi-GPU communication, and adaptive mesh refinement. She leads the Parallel and Multicore Computing Lab , driving innovations in exascale co-design and heterogeneous system optimization. ACM SIGHPC Emerging Woman Leader in Technical Computing Award (2021) ERC Starting Grant (1.5M EUR) for the SparCity Project (2025) EuroHPC Grant for Extreme Scale Technologies and Applications (2025) 2025 BAGEP Award (Science Academy) Her work bridges Computer Architecture and Machine Learning , addressing challenges in data locality , multi-GPU systems , and performance portability . Recent publications highlight trends in sparse tensor optimization , asynchronous AMR execution , and compiler support for heterogeneous memory . She has developed tools like ComScribe for intra-node GPU communication analysis and ReuseTracker for multicore reuse distance analysis. Dr. Unat’s research is supported by grants from ERC and EuroHPC , reflecting her leadership in exascale technologies and GPU-centric systems . She contributes to the evolution of tiling abstractions , dynamic LLM training , and lightweight communication detection for modern architectures.

• High Performance Computing (HPC)
• Data Locality
• GPU Computing
• +۷ مورد دیگر

Prof. Banu Günel Kılıç is a full-time faculty member at Middle East Technical University (METU), where she holds the rank of Professor in the Graduate School of Informatics, Department of Information Systems. She has served in various academic roles since 2004, including previous appointments as Associate Professor (2014-2022) and Assistant Professor (2010-2014), and currently directs the Graduate School of Informatics. Doctorate: Queen's University of Belfast (2001-2004) Postgraduate: University of Bristol (2000-2001) Undergraduate: METU, Electrical Engineering (1995-2000) Her research focuses on signal processing, cybersecurity, and machine learning, with particular emphasis on intrusion detection systems in software-defined networks, acoustic gunshot localization, auditory attention modeling, and security visualization infrastructures. She has supervised 14+ graduate theses, including work on microservice call graphs and institutional investor networks. Recent publications demonstrate strong interdisciplinary work in machine learning and cybersecurity , with specific applications in intrusion detection, cloud resource allocation, and acoustic signal processing. She has contributed to over 25 peer-reviewed publications and holds two standard patents in acoustic source separation technology. Prof. Kılıç has participated in multiple European Union funded projects including EuroCC2 (2023-2026), EUMaster4HPC (2022-2025), and prior FP7 projects like IRIS and DIOMEDES. Her work bridges traditional acoustic signal processing with modern cybersecurity applications in enterprise environments.

• Signal Processing
• Artificial Intelligence
• Software Engineering
• +۴ مورد دیگر

Onur Demirörs is a Professor and Chair of the Computer Engineering Department at Izmir Institute of Technology. His academic journey includes a B.Sc. from Middle East Technical University (1987), two M.Sc.s (Ege University, 1990; Southern Methodist University, 1993), and a Ph.D. from Southern Methodist University (1995). He has held academic positions at institutions like Dokuz Eylül University and Middle East Technical University before joining Izmir Institute of Technology in 2017. His research focuses on software process improvement , business process management , software quality , and microservices architecture . Notable projects include developing the BIM-CAREM model for construction industry process assessment and leading a TÜBİTAK-funded project on microservice-based software size measurement. Recent publications emphasize agile methodologies , microservices , and software measurement . His work bridges academic research with industry practice, such as exploring event-driven systems and effort estimation techniques. He teaches courses like Software Engineering and Microservice-Based Systems Analysis . Key contributions include advancing process modeling frameworks (e.g., Plural ), tool development for functional size estimation ( EFES ), and integrating ontologies with business processes ( PROMPTUM ). His research often addresses challenges in software lifecycle management, process automation, and cross-domain collaboration.

• Software Engineering
• Software Process Improvement
• Business Process Management
• +۴ مورد دیگر

Ezgi Aydemir serves as a Lecturer in the Department of Algebra and Number Theory within the Faculty of Arts and Sciences at Iğdır University. Her academic profile combines rigorous teaching with specialized research in graph theory and its applications. Education: Doctorate (2013-2018): Selcuk University, Institute of Science/Mathematics/Algebra and Number Theory Department; Thesis: 'New parameters in graphs and some results' Master's Degree (2010-2013): Selcuk University, Institute of Science/Mathematics (MA) with Thesis; Thesis: 'Some parameters in graphs and their relations' Bachelor's Degree (2005-2010): Balikesir University, Faculty of Arts and Sciences/Department of Mathematics Research Focus: Dr. Aydemir's scholarly work centers on graph theory with particular emphasis on topological indices, spectral graph properties, and applications in mathematical chemistry. Her research investigates various graph invariants including Co-PI indices, Zagreb indices, harmonic indices, and spanning trees. She has recently expanded her research to include applications of AI techniques like GPT-4 for sentiment analysis through mathematical modeling, demonstrating interdisciplinary reach beyond traditional graph theory. Publication Trends: Dr. Aydemir's research output shows a clear progression from foundational work on Co-PI indices (2015-2017) to more complex spectral analyses (2018) and recently to interdisciplinary applications (2021-2024). Her publications consistently address theoretical aspects of graph invariants while increasingly exploring practical applications in chemistry and computational fields. The 2024 paper applying differential equations and GPT-4 to sentiment analysis represents a significant expansion of her research scope. Teaching and Administration: At Iğdır University, Dr. Aydemir teaches a comprehensive range of mathematics courses including Graph Theory (graduate level), Abstract Algebra, Linear Algebra, and Number Theory. She has held significant administrative positions as Department Vice Chair (2020) and Dean's Assistant (2019), demonstrating leadership and commitment to institutional development. Her course portfolio reflects both deep theoretical knowledge and practical teaching skills across multiple levels of mathematics education.

• Graph Theory
• Algebraic Graph Theory
• Topological Indices
• +۲ مورد دیگر