جست‌وجوی استاد و پژوهشگر

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.

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.

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.

• Artificial Intelligence
• Medical Imaging
• Deep Learning
• +۳ مورد دیگر

Caner Özer is a Researcher affiliated with Istanbul Technical University's Department of Artificial Intelligence and Data Engineering and the University of Twente's MIA group. He holds a PhD in Computer Engineering from Istanbul Technical University (2020), an MSc in Telecommunication Engineering (2017-2020), and a BSc in Electronics and Communications Engineering (2013-2017). His research focuses on medical imaging AI, explainable artificial intelligence (XAI), deep learning applications in healthcare, and computer vision techniques for artifact detection in medical imaging. He has conducted visiting research at the University of Twente (2024) and serves on academic committees at Istanbul Technical University. Research interests include developing explainable models for mammogram analysis, enhancing medical image quality assessment via transformers and neural networks, and addressing challenges in cardiovascular MRI segmentation through motion artifact detection. His work bridges deep learning theory with practical clinical applications, emphasizing transparency and accuracy in AI-driven medical diagnostics. Notable contributions include cross-domain artifact correction for cardiac MRI, joint CNN-RNN models for intracranial hemorrhage detection, and XAI methods for chest X-ray analysis. His research has been published in top-tier venues with a focus on medical imaging and deep learning advancements.

• Computer vision
• Machine learning
• Statistical data analysis
• +۳ مورد دیگر

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.

Selda Güneyمشاهده پروفایل

استادیار

• Machine Learning
• Signal Processing
• Image Processing
• +۳ مورد دیگر

Selda Güney is an Assistant Professor in the Department of Electrical and Electronics Engineering at Başkent University's Faculty of Engineering. She holds a PhD (2013), Master's (2007), and Bachelor's (2004) in Electrical-Electronics Engineering from Karadeniz Technical University. Her professional experience includes roles as an R&D Engineer at DEKA Digital (2004-2005), Research Assistant at Karadeniz Technical University (2005-2013), and Assistant Professor at Başkent University (2013-present). Her research spans: Machine Learning : Applications in medical imaging, radar, and industrial systems Signal/Image Processing : Focus on real-time classification and fault detection Pattern Recognition : Electronic nose systems and biometric analysis Her recent publications demonstrate strong emphasis on deep learning applications in healthcare (chest X-ray classification, fracture detection) and industrial automation (real-time fault detection systems). Over 70% of her last 15 articles involve medical/industrial AI implementations using convolutional networks. Awards & Honors: TÜBİTAK Domestic PhD Scholarship IBEC ERASMUS Scholarship Research Leadership: Supervised 20+ graduate theses (e.g., radar data classification, medical image steganography) and led 9 R&D projects including: AI-based pathology classification in lung X-rays VR glove development Smart parking systems She is a member of IEEE and ISOCS, and teaches courses including Pattern Recognition, Signals and Systems.

• Signal Processing
• Image Processing
• Machine Learning
• +۵ مورد دیگر

Prof. Dr. Bilge Günsel is a distinguished Professor at the Electronics and Communication Engineering Department of Istanbul Technical University . With a career spanning over three decades, she has served in academic and administrative roles including Department Head (2007-2010) and Deputy Head (2005-2006). Her research focuses on Signal Processing , Image Processing , and Machine Learning , with recent work on dynamic convolutional neural networks and video object tracking. Education : PhD (1994) and BS (1985) from Istanbul Technical University in Electronics & Communication Engineering. Research Interests include: Dynamic CNNs for scene classification Video object tracking with deep learning Meta-learning approaches in object verification Transfer learning for crowd density estimation Recent Publications (2021-2024) demonstrate expertise in: Target-driven inference in video tracking Dynamic convolution techniques Instance segmentation integration Scientific Achievements : Scopus h-index of 18 Over 1252 citations Principal Investigator (PI) for two major BAP projects (2016-2019) Collaborations span Turkey and international institutions, with research outputs in partnership with IEEE and academic peers like Furkan Gurkan and Yavuz K. Hanoglu. She continues to lead cutting-edge research while maintaining active teaching and administrative duties.

BÜLENT HAZNEDARمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Fuzzy Logic
• +۵ مورد دیگر

Bülent Haznedar is an Associate Professor in the Department of Computer Engineering at Gaziantep University's Faculty of Engineering, a position he has held since 2024. Previously, he served as Doctor Lecturer at Gaziantep University (2021-2024) and held academic positions at Hasan Kalyoncu University (2013-2021) and Erciyes University (2011-2013), where he progressed from Lecturer to Department Head. His educational qualifications include: Doctorate in Computer Engineering from Erciyes University (2011-2017) Master's degree in Computer Engineering from Erciyes University (2007-2010, with thesis) Licence degree in Computer Engineering from Erciyes University (2003-2007) Dr. Haznedar's research centers on Artificial Intelligence and Machine Learning applications, with significant contributions in hydrological modeling (streamflow forecasting using hybrid ANFIS algorithms), renewable energy (solar radiation optimization), medical diagnostics (thyroid nodule classification and cancer detection), and cultural heritage informatics (3D point cloud segmentation for historical buildings). His work consistently integrates fuzzy logic systems with metaheuristic optimization techniques to solve complex prediction problems. Analysis of his 29 journal articles (2016-2024) reveals a dominant focus on Adaptive Neuro-Fuzzy Inference Systems enhanced by evolutionary algorithms (PSO, GA, ABC) across hydrology and medical domains, with recent expansion into sustainable energy and heritage preservation. His publications show increasing interdisciplinary collaboration, particularly in TUBITAK-funded projects. His scientific recognition includes: TUBITAK Publication Encouragement Awards (2018, 2023) TUBITAK PhD Scholarship (2011) TUBITAK Master's Scholarship (2008) Dr. Haznedar has supervised eight master's theses on AI applications in streamflow forecasting, energy prediction, cancer classification, and heritage modeling. His research is supported by seven projects, most notably the TUBITAK 1001 project (2019-2023) developing Heritage Building Information Modeling for Turkey's cultural heritage restoration. He also contributed to TUBITAK's Digital Prosthesis Workshop initiative. While specific laboratory affiliations aren't detailed, his leadership in the TUBITAK cultural heritage project indicates active collaboration with multidisciplinary teams spanning engineering, computer science, and heritage conservation disciplines.

• Computer Vision
• Image Processing
• Medical Informatics
• +۳ مورد دیگر

Dr. Faris Serdar TAŞEL is an Assistant Professor at Cankaya University's Faculty of Engineering and Architecture, Department of Computer Engineering. He holds a Ph.D. in Medical Informatics from Middle East Technical University (2016) and has expertise in Computer Vision and Image Processing. His research focuses on medical image analysis, particularly mitochondria segmentation from electron microscope tomography. Education: B.Sc. in Computer Engineering, Cankaya University (2004) M.Sc. in Computer Engineering (3D Reconstruction Using Stereo Images), Cankaya University (2008) Ph.D. in Medical Informatics (Detection and Segmentation of Mitochondria from Electron Microscope Tomography Images), Middle East Technical University (2016) Research Interests: Combining computer vision techniques with medical imaging challenges, including 3D reconstruction, medical image processing, and automated analysis tools for biological structures like mitochondria. His work bridges engineering and biomedical sciences to develop practical software solutions for microscopic image analysis. Awards: 2016-2017 METU Thesis of the Year Award for doctoral research Labs/Teams: Active in medical image processing research groups, focusing on developing tools like MitoSeg for mitochondrial analysis in electron microscopy.

• Artificial Intelligence
• Robotics
• Computer Vision
• +۴ مورد دیگر

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.

Enes Ayanمشاهده پروفایل

مدرس

• Artificial Intelligence
• Deep Learning
• Medical Image Analysis
• +۳ مورد دیگر

Enes Ayan serves as a Doctor Lecturer in the Department of Computer Engineering at Kirikkale University's Faculty of Engineering and Natural Sciences, where he has maintained continuous academic affiliation since his 2014 appointment as Research Assistant. His career trajectory includes completing both master's (2015) and doctoral degrees (2019) in Computer Engineering at the same institution following his 2013 bachelor's graduation from Süleyman Demirel University. Education Bachelor's: Computer Engineering, Süleyman Demirel University (Isparta), 2013 Master's: Computer Engineering, Kirikkale University, 2015 Doctorate: Computer Engineering, Kirikkale University, 2019 Research Focus Dr. Ayan's work centers on deep learning applications across three primary domains: medical imaging (specializing in dental diagnostics, radiology, and endoscopy), security systems (weapon detection and traffic monitoring), and agricultural technology (crop pest classification). His research bridges theoretical AI advancements with practical healthcare solutions, particularly through explainable AI frameworks for dental caries detection and pneumonia diagnosis. Publication Trends Analysis of his 15 most recent publications (2020-2025) reveals intensifying specialization in dental AI applications (60% of 2024-2025 output), with significant contributions to caries detection under prostheses and tooth numbering systems. Concurrently, his work maintains strong threads in security-focused computer vision (UAV-based traffic analysis, weapon detection) and agricultural AI, demonstrating methodological versatility through genetic algorithm optimizations and ensemble CNN architectures. Professional Context No information regarding student supervision, research grants, laboratory facilities, or scientific awards appears in the source materials. His academic progression from Research Assistant to Doctor Lecturer indicates standard career advancement within Kirikkale University's engineering faculty without notable interruptions.

Hasan Aksoyمشاهده پروفایل

دانشیار

• Marketing
• Consumer Behavior
• Industrial Marketing
• +۷ مورد دیگر

Dr. Hasan Aksoy is an Associate Professor at Gaziantep University, Faculty of Economics and Administrative Sciences, Department of International Trade and Logistics. He has held roles including Domestic Deputy Director of the Institute (2017-2020) and Domestic Head of Department (2014-present). PhD in Business Administration, Selçuk University (2011) MSc in Business Administration, Selçuk University (2004) BSc in Business Administration, Uludağ University (2000) His research focuses on marketing strategies, consumer behavior, supply chain dynamics, and innovation in SMEs. He has extensively studied luxury consumption patterns, social media advertising effectiveness, and cluster-based competitive advantage. Key article trends include: luxury brand psychology (2021-2023), innovation culture in SMEs (2016-2017), supply chain ethics (2017), and social media marketing (2021). No specific awards are mentioned. Notable projects: Turquality® (2019), Gaziantep Innovation Survey (2015), Olive Pomace Market Research (2016), and Japan Market Marketing Strategy (2019). He has supervised 4 completed and 1 ongoing graduate theses.

Mehmet Berk Atamanمشاهده پروفایل

دانشیار

• Marketing Analytics
• Marketing Mix Modeling
• Marketing and Consumer Behavior Dynamics
• +۳ مورد دیگر

Mehmet Berk Ataman is an Associate Professor of Marketing at Özyeğin University's Faculty of Business, where he teaches Marketing Management, Research Methods, and Marketing Research courses across MBA, EMBA, and PhD programs. Previously, he held academic positions at Koç University (2013-2022), Rotterdam School of Management (2006-2013), Tilburg University (2002-2006), and Istanbul Technical University (1999-2002). Education: PhD in Marketing, Tilburg University, 2007 MSc in Management Engineering, Istanbul Technical University, 2002 BSc in Management Engineering, Istanbul Technical University, 1998 Dr. Ataman is an expert in developing quantitative models to support marketing decisions, with research focusing on how managers can make decisions that positively impact brand and firm performance over the long term. His work spans marketing analytics, marketing mix models, consumer behavior dynamics, and brand management. He has developed a strong research program investigating the long-term effects of marketing strategies on brand performance, mobile marketing dynamics, and brand architecture. His research output shows a clear progression from foundational work on brand building and marketing strategy effects to contemporary research on mobile marketing, digital consumer behavior, and social media analytics. Recent publications demonstrate his adaptation to evolving digital landscapes while maintaining focus on core marketing principles and long-term brand effects. Awards and Recognition: 2017 ISMS Long-term Impact Award 2009 ERIM Top Article Award 2008 Citation of Excellence Award Emerald/EFMD Outstanding Doctoral Research Award EUR Fellowship (2009) Marketing Science Institute's Young Scholars Program (2011) Finalist for 2008 John DC Little Award Finalist for 2015 Annual William F. O'Dell Award Dr. Ataman serves on the editorial board of MarkTech: The Journal of Marketing and Technology and previously served on the International Journal of Research in Marketing (2009-2015). He holds a Participant-Centered Learning certificate from Harvard Business School and applies this teaching methodology across his MBA, EMBA, and executive education courses. His research has been published in top journals including Journal of Marketing Research, Marketing Science, and International Journal of Research in Marketing.

• Biomedical Engineering
• Machine Learning
• Medical Imaging
• +۳ مورد دیگر

Burcu Oltu is a Researcher in the Biomedical Engineering Department at Başkent University. She holds both a Master's Degree (2020) and Bachelor's Degree (2017) from the same institution. Her work focuses on applying machine learning techniques to biomedical signal processing and medical imaging. Education: MSc & BSc in Biomedical Engineering, Başkent University Email: boltu@baskent.edu.tr Her research integrates machine learning with biomedical engineering to solve medical diagnostic challenges. Key areas include: Deep learning for pulmonary disease classification from chest X-rays EEG signal analysis for Alzheimer's disease detection Transfer learning approaches for diabetic retinopathy detection Photoplethysmography and blood pressure signal analysis for sleep apnea detection Heart sound signal processing using wavelet transforms Her publications demonstrate a strong focus on developing AI-powered diagnostic tools for various medical conditions, with recent work appearing in journals like BMC MEDICAL IMAGING and Biomedical Signal Processing and Control. She has received recognition for her work, including: Bronze Medal - Istanbul International Invention Fair (ISIF) 2021 Burcu collaborates with researchers like Prof. Dr. Berna Dengiz and Doç. Dr. Selda Güney on projects involving medical imaging analysis and physiological signal processing. Her technical expertise spans algorithm development, neural networks, and biomedical device design.

• Computer Science
• Artificial Intelligence
• Digital Art Analysis
• +۳ مورد دیگر

Baybora Temel is an Associate Professor at Trakya University Faculty of Fine Arts , with a PhD in Computer Science from Marmara University (2009). His research merges Artificial Intelligence and Digital Art Analysis , focusing on Art Authentication via wavelet transforms and neural networks. Specializes in Painting Style Classification and Digital Art Forensics Recipient of Nuri Iyem Painting Competition Exhibition (2015) and Australian Embassy Painting Award (2009) Active in International Art Symposia (Odessa, Patras) and National Exhibitions His 15 most recent publications span Art Authentication (2008-2022) and Digital Art Analysis , employing Machine Learning for Cubist Painting Discrimination and Figurative Art Studies . He has curated exhibitions like Art Suites 26th International Art Workshop (2018) and participated in Balkan Exhibitions IV (2023).