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.

Ozcan Ozturkمشاهده پروفایل

استاد

• Heterogeneous Computing
• Hardware Accelerators
• GPU Computing
• +۷ مورد دیگر

Ozcan Ozturk is a Professor in the Computer Science and Engineering and Electronics Engineering programs at Sabancı University's Faculty of Engineering and Natural Sciences. Previously, he held professorships at Bilkent University and adjunct roles at North Carolina State University. His expertise spans heterogeneous computing, parallel systems, processor architecture, and compiler optimization. He earned his Ph.D. from Penn State University, with prior academic roles at the University of Florida and internships at Intel and Marvell. Education: Ph.D. in Computer Science and Engineering (2007), Pennsylvania State University M.S. in Computer Engineering (2002), University of Florida B.Sc. in Computer Engineering (2000), Bogazici University Research interests include accelerator technologies, GPU-based systems, multicore processors, and compiler optimizations. His work focuses on improving parallelization efficiency, energy optimization, and reliability in heterogeneous architectures. He leads funded projects like 'Machine Learning for Compiler Flags' and 'Graph Accelerator Design'. Notable awards include the Bilkent Teaching Award (2019), BAGEP (2018), and HiPEAC Paper Award (2016). He serves on editorial boards of IEEE and ACM journals and chairs major conferences like ASPLOS and ICS. Grants and collaborations include partnerships with Huawei, Intel, NVIDIA, and TÜBİTAK. He advises over 20 students and has supervised projects in safety-critical systems, FPGA accelerators, and compiler-directed optimizations. His lab develops domain-specific architectures, including RISC-V extensions for graph processing.

Aykut Erdemمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Aykut Erdem is an Associate Professor of Computer Engineering at Koç University, affiliated with the KUIS AI Center. He earned his PhD, MSc, and BSc in Computer Engineering from Middle East Technical University (METU), with visiting researcher experiences at Virginia Tech (2004) and MIT (2007). His research focuses on learning-based approaches for visual data understanding, including image editing, visual saliency estimation, and vision-language integration. Research Interests: Vision and Graphics, Machine Learning, Artificial Intelligence, Computer Vision, Natural Language Processing, Generative Artificial Intelligence. Recent work includes text-guided image/video editing, diffusion models for object removal, and GAN-based frameworks for domain adaptation. Scientific Awards: Young Scientist Award (BAGEP 2021) by Science Academy in Computer Engineering Best Paper Award at 5th Multimodal Learning and Applications Workshop (2022) Collaborations and Funding: Principal investigator for TUBITAK 1001 project on generative AI for visual data (2021-2024), Adobe Research Gift (2023), and co-investigator for multiple TUBITAK grants. Serves as Associate Editor for IEEE Transactions on Image Processing (2022-present).

Erkut Erdemمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Visual Saliency Prediction
• +۵ مورد دیگر

Erkut Erdem is a Professor in the Department of Computer Engineering at Hacettepe University, where he leads the Computer Vision Laboratory (HUCVL). His research focuses on computer vision and machine learning, particularly on incorporating different kinds of context (spatial, temporal and cross-modal) into visual processing across all levels from low to high-level vision. He received his Ph.D. (2008), M.Sc. (2003), and B.Sc. (2001) from Middle East Technical University. Prior to joining Hacettepe University in 2010, he completed a post-doctoral fellowship at Ecole Nationale Supérieure des Télécommunications (2009-2010) and held visiting researcher positions at UCLA (2007) and Virginia Tech (2004). His current research interests include Visual Saliency Prediction, Automatic Image Description, Video/Photoset Summarization, Image Filtering, and Image Editing. Recent work has focused on multimodal learning with video-language models, diffusion-based image editing, and event-based vision for low-light conditions. His research has been published in top venues including NeurIPS, ICLR, ICCV, SIGGRAPH, and ACL. He has received significant recognition including The Young Researcher Award from Turkish Academy of Sciences and being named a 2022 Outstanding Associate Editor of IEEE Transactions on Multimedia. He has secured multiple research projects funded by TUBITAK and received gift funds from Adobe Research for text-guided image synthesis work. Current Teaching: BBM202: Algorithms, AIN434/BBM444: Fundamentals of Computational Photography Graduate Supervision: 6 current Ph.D. students, numerous recent graduates including Burak Ercan (2024) and Aysun Kocak (2023) Professional Affiliations: Co-affiliated with Koç University and İş Bank AI Center (KUIS AI)

• Computational Design
• Architectural Education
• Artificial Intelligence in Architecture
• +۹ مورد دیگر

Assoc. Prof. Dr. Sema Alaçam Doğan has been affiliated with Istanbul Technical University since 2014, serving as an Associate Professor in the Department of Architecture . She has held administrative roles including Deputy Head of Department and Erasmus Coordinator. Education : PhD in Informatics in Architectural Design (2008-2014), MS in Informatics in Architectural Design (2005-2008), and BS in Architecture (1999-2005) from Istanbul Technical University. Her research explores Computational Design , Artificial Intelligence in Architecture , and Sustainable Material Innovation . She investigates digital tools for heritage preservation, daylight optimization in BIM, and cognitive development in architecture students. Recent publications analyze AI-assisted design literacy , machine learning for Sinan mosques , and environmental comfort in Harran houses . Her work integrates algorithmic frameworks with sustainable practices. Scientific awards include multiple ITU Publication and Performance Awards (2021-2024), FABFEST Prizes , and the 2024 Artemis Educator Award from NASA. Active projects like "Physical Computation in Architectural Drawing" and "Robotic Fabrication with Recycled Wind Turbine Blades" demonstrate her leadership in computational and sustainable research.

İsmail ÖZTELمشاهده پروفایل

استادیار

• Artificial Intelligence
• Deep Learning
• Image Processing
• +۳ مورد دیگر

Dr. İsmail ÖZTEL serves as an Assistant Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences. He has been a faculty member since 2019, following his tenure as a Research Assistant from 2012-2019 at the same institution. His educational background includes: Doctorate in Computer and Information Engineering (2014-2018) from Sakarya University with thesis on "Facial expression detection on partial and full face images using machine learning methods" Master's Degree in Computer and Information Engineering (2012-2014) from Sakarya University with thesis on "Driver simulator for educational purposes" Bachelor's Degree in Computer Engineering (2007-2011) from Sakarya University Dr. ÖZTEL's research focuses on artificial intelligence, deep learning, and computer vision with significant applications in healthcare, mobile technology, and public safety. His work has evolved from foundational facial expression recognition to sophisticated medical applications including skin disease classification using smartphones, monkeypox detection from skin lesions, and pandemic response systems for face mask detection. His research demonstrates strong interdisciplinary connections between computer science and healthcare. An analysis of his publication trends reveals a clear progression toward increasingly complex deep learning architectures applied to real-world problems, with recent work emphasizing medical applications using mobile technology and public health safety systems. His 2023-2025 publications show particular focus on skin disease classification, intelligent vehicle systems, and hybrid feature extraction methods for pandemic response. Dr. ÖZTEL has served as a reviewer for numerous prestigious journals including Expert Systems With Applications (multiple years), World Wide Web, Multimedia Tools and Applications, and Journal of King Saud University - Computer and Information Sciences, demonstrating his recognition in the academic community across multiple domains. His research projects include work on facial expression detection in open scientific databases (2020), performance evaluation of transfer learning approaches (2019), and current projects on brain tumor classification systems and earthquake safety education for individuals with developmental disabilities. His international research experience includes collaboration with Filiz Bunyak in 2017, indicating global engagement in his field.

• Cybersecurity
• Maritime Cyber Risk Assessment
• Dynamic Positioning Systems
• +۱۲ مورد دیگر

Pelin Bolat is an Associate Professor in the Department of Fundamental Sciences at Istanbul Technical University (ITU), College of Maritime Studies. She is actively engaged in maritime cybersecurity, risk assessment, and maritime safety research. Her work is supported by multiple BAP and EU-funded projects, with ongoing research extending into 2025. Her research interests include cybersecurity in maritime navigation systems, dynamic positioning, port state control, and GHG emissions in the maritime sector. She applies advanced methodologies such as fuzzy FUCOM, CORAS framework, and association rule mining to analyze cyber and operational risks. Her recent publications (2023–2025) reflect a strong trend in maritime cybersecurity, focusing on ECDIS, RADAR, ransomware, and cyber hygiene. These works span high-impact journals in maritime engineering and technology, demonstrating interdisciplinary engagement with computer science, safety engineering, and policy analysis. She serves as a principal investigator on several key projects, including cyber risk assessment of bridge navigation equipment and system dynamic modeling of maritime GHG emission measures. She also mentors 15 theses in progress, indicating her active role in student supervision. Her collaborative network includes researchers like Gökhan Kayişoğlu and international partners. While no formal awards are listed, her leadership in EU and BAP projects underscores her academic prominence.

Mustafa Asım Kazancıgilمشاهده پروفایل

استادیار

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

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

• Deep Learning
• Self-supervised learning
• Efficient training of deep learning methods
• +۳ مورد دیگر

Mustafa Taha Koçyiğit is a Full-time Assistant Professor at Bogazici University. His research focuses on Deep Learning, Self-supervised learning, Efficient training of deep learning methods, Computer vision, Efficient training of large language models, and Language grounded vision models. His recent work addresses computational efficiency in training methods and novel applications of deep learning across domains like aerospace defect detection and computer vision. His publications span advancements in self-supervised learning strategies (2023), efficient training for computer vision tasks (2023), and theoretical contributions like unsupervised batch normalization (2020). The 2025 work demonstrates cross-disciplinary impact in aerospace engineering through AI-driven defect detection via X-ray tomography. Notable Contributions: Bridging efficiency and accuracy in deep learning pipelines Technical Strengths: Neural architecture design, optimization strategies, and domain-specific model adaptation

Aykut Koçمشاهده پروفایل

دانشیار

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

• Signal Processing
• Communication
• Wireless Communications
• +۴ مورد دیگر

Professor Hakan Ali Çırpan is a distinguished faculty member at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where he serves as Professor in the Department of Electronics and Communication Engineering. He also holds the position of Vice Dean at Istanbul Technical University since 2021. With over three decades of academic experience, Professor Çırpan has established himself as a leading researcher in signal processing and communications. His educational background includes: PhD from Stevens Institute of Technology (1993-1997) Master's degree in Electrical-Electronic Engineering (with thesis) from Istanbul University (1989-1992) Bachelor's degree in Electrical and Electronic Engineering from Uludağ University (1985-1989) Professor Çırpan's research spans multiple domains within signal processing and communications. His primary interests include wireless communications, radar systems, machine learning applications in communications, and electronic warfare. His work on channel estimation, orthogonal frequency division multiplexing, and maximum likelihood methods has been particularly influential. He has pioneered research in areas such as source localization, spectrum sensing, and physical layer security. His recent work focuses on 5G/6G networks, AI-enhanced communications, and integrated sensing and communication systems. Analysis of his recent publications (2023-2025) reveals a strong focus on next-generation wireless technologies, particularly 5G/6G networks, AI integration in communications, and electronic warfare applications. His research demonstrates a consistent pattern of addressing fundamental challenges in signal processing while adapting to emerging technological needs. A significant portion of his recent work involves machine learning applications for spectrum management, optimization techniques for radar systems, and novel approaches to network slicing and resource allocation. His notable scientific achievements include: ASELSAN ACADEMY THESIS COMPETITION WINNER (2020) Professor Çırpan has supervised 59 theses throughout his career, mentoring numerous graduate students in the fields of signal processing and communications. He has secured significant research funding, including the "AI-Enhanced 5G/6G Networks with Integrated Camera and ISAC Systems" project (2023-2024) and the "Railway Vehicle Infrastructure New Generation Secure Communication Systems" TÜBİTAK project with a budget of ₺955,000. His research has practical applications in defense systems, railway communications, and next-generation wireless networks. His laboratory work focuses on wireless communications systems, radar signal processing, and AI-enhanced communication technologies. Professor Çırpan leads research teams working on projects related to 5G/6G networks, electronic warfare countermeasures, and secure communication systems. His group collaborates with industry partners like ASELSAN and conducts research with practical applications in national defense and critical infrastructure.

Ali Yaparمشاهده پروفایل

استاد

• Electromagnetics
• Microwave Engineering
• Antenna Technologies
• +۳ مورد دیگر

Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.

Emre Seferمشاهده پروفایل

دانشیار

• Bioinformatics
• Machine Learning
• Financial Networks
• +۳ مورد دیگر

Dr. Emre Sefer is an Associate Professor at the Faculty of Engineering, Özyeğin University, specializing in machine learning and bioinformatics. He holds a Ph.D. in Computational Biology from Carnegie Mellon University (2015), an M.S. in Computer Science from University of Maryland College Park (2011), and a B.S. in Computer Engineering from Boğaziçi University (2008). His research bridges graph machine learning with financial networks, bioinformatics, and data engineering. Ph.D.: Computational Biology, Carnegie Mellon University M.S.: Computer Science, University of Maryland College Park B.S.: Computer Engineering, Boğaziçi University Research focuses on applying machine learning to financial and biological networks: Bioinformatics : 3D genome modeling, protein modifications, transcriptomic analysis Graph Machine Learning : GNNs for fraud detection, drug response prediction, and network evolution Financial Networks : Cryptocurrency investment strategies, asset price prediction His lab (OzU Machine Learning in Finance and Bioinformatics Lab) develops graph-based deep learning methods for cross-domain applications, including NFT market analysis and chromatin structure prediction. He received the Best research paper award at Recomb 2016 for work on 3D genome architecture. Former postdoc at CMU Machine Learning Department Industry experience as Quantitative Strategist at Goldman Sachs and JPMorgan

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

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

Ahmet ÖZMENمشاهده پروفایل

استاد

• Computer Vision
• Traffic Monitoring Systems
• Sensor Systems
• +۶ مورد دیگر

Prof. Dr. Ahmet ÖZMEN is a Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Software Engineering. He has held various administrative positions including Head of the Software Engineering Department (2019-2028) and Director of the Computer Research and Application Center (2019-2022). With extensive experience in academia since 1991, he has made significant contributions to computer vision, traffic monitoring systems, and sensor technologies. Sakarya University: Professor (2019-present), Associate Professor (2011-2019) Dumlupınar University: Assistant Professor (2001-2011), Research Assistant (2000-2001, 1993-1998) Istanbul Technical University: Research Assistant (1991-1993) Prof. ÖZMEN's research spans computer vision applications for traffic monitoring, indoor air quality systems, parallel computing, and sensor technologies. His work bridges theoretical computer science with practical engineering applications, particularly in developing vision-based systems for nighttime vehicle detection, traffic flow monitoring, and environmental sensing. His interdisciplinary approach combines machine learning, image processing, and embedded systems to solve real-world problems in transportation and environmental monitoring. His publication record shows a clear evolution from parallel and distributed systems in his early career to computer vision and sensor applications in recent years. The majority of his recent work focuses on traffic monitoring systems using computer vision techniques, particularly for nighttime conditions, and indoor air quality monitoring systems using sensor networks. His research demonstrates strong industry and societal relevance, with applications in smart transportation, environmental protection, and educational technology. TÜBİTAK Publication Awards (2006, 2008, 2009, 2010) Physical implementation award from TÜBİDER (2008) Microsoft Certified Professional Certificate (2005) YÖK overseas study scholarships (1993, 1998) Elginkan graduate scholarships (1990, 1991) Prof. ÖZMEN has supervised numerous graduate students across multiple institutions, with a focus on practical engineering problems. His research has been supported by various projects including TÜBİTAK projects, institutional research grants, and industry collaborations. He has led significant research initiatives in traffic monitoring systems, indoor air quality monitoring, and educational technology platforms. His administrative leadership has included directing research centers and shaping curriculum development in software engineering. His work has involved establishing research teams focused on computer vision applications, sensor network development, and educational technology. These teams have produced numerous publications, developed practical systems, and trained the next generation of computer engineers. Current research directions include advanced traffic monitoring systems using deep learning and multi-camera setups for urban planning applications.