جست‌وجوی استاد و پژوهشگر

• Food Sciences
• Food Engineering
• Food Chemistry
• +۳ مورد دیگر

Assoc. Prof. Dr. Ceyda Dadali serves as a faculty member in the Department of Food Engineering at Ege University's Faculty of Engineering, Turkey, holding the academic rank of Associate Professor. Her research spans sustainable food processing and product development with institutional recognition through metrics including an h-index of 6 and 65 Web of Science citations. Her research interests encompass Food Sciences , Food Engineering , Food Chemistry , Sensory Science , Sustainable Food Processing , and Food Product Development . She investigates gluten-free formulation optimization, sugar/fat reduction strategies, and valorization of food byproducts (e.g., artichoke bracts, eggshells), employing techniques like response surface methodology for multifactorial optimization and volatile compound analysis for food authentication. Analysis of her recent publications (2021-2025) reveals consistent focus on healthier food systems through ingredient substitution, waste valorization, and sensory engineering. Her work demonstrates expertise in balancing nutritional improvements with sensory acceptance, particularly in baked goods and beverages, while addressing sustainability goals through agricultural byproduct utilization. Dr. Dadali has contributed to 8 projects involving intellectual property and designs, with extensive institutional collaboration evidenced by 8 primary in-house research partners. Her professional activities include 3 documented experiences and 5 educational qualifications, though specific details remain undisclosed in available sources.

Serap ÇAKAR KAMANمشاهده پروفایل

استادیار

• Computer vision
• Deep learning
• Object detection
• +۶ مورد دیگر

Serap ÇAKAR KAMAN is an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Computer Engineering. She has maintained a continuous academic career at the university since 2000, progressing from Research Assistant to Lecturer and finally to Assistant Professor. Her educational background includes: Doctorate in Electrical Engineering (2003-2009) from Sakarya University Institute of Science with thesis on "DIGITAL IMAGE WATERMARKING METHODS BASED ON MOMENT-BASED NORMALIZATION" Master's in Computer and Information Engineering (2000-2003) from Sakarya University Institute of Science with thesis on "DETECTING, TRACKING AND TARGET IDENTIFICATION OF OBJECT MOVEMENTS ON VIDEO IMAGES" Bachelor's in Electrical-Electronics Engineering (1996-2000) from Sakarya University Faculty of Engineering Dr. ÇAKAR KAMAN's research spans multiple domains within computer vision and artificial intelligence, with particular expertise in object detection, deep learning applications, and image processing. Her work bridges theoretical computer vision with practical applications in industrial automation, medical imaging, and electric vehicle technology. She has made significant contributions to metal surface defect detection, autonomous charging systems, and facial expression recognition for healthcare applications. Her research demonstrates a consistent pattern of applying advanced computer vision techniques to solve real-world problems across diverse domains. Analysis of her publication trends reveals a clear evolution from foundational work in digital image watermarking to cutting-edge applications of deep learning in industrial settings. Her recent publications (2023-2025) focus on practical implementations in agricultural technology (hazelnut kernel analysis), business intelligence (employee feedback analysis), and marine infrastructure (shore-to-ship charging). The consistent thread through her research is the development of robust computer vision algorithms that enhance automation and precision in various technical contexts. With an H-index of 4 in Web of Science and 114 citations, Dr. ÇAKAR KAMAN maintains an active research profile. Her academic contributions include teaching in the Department of Computer Engineering and likely supervision of graduate students, though specific student information isn't documented in the available materials. Her work contributes significantly to Sakarya University's research profile in computer engineering and supports Turkey's growing expertise in artificial intelligence applications. Her laboratory work appears to focus on computer vision systems with emphasis on real-time processing applications. The research groups she participates in likely include teams working on industrial automation, electric vehicle infrastructure, and medical image analysis, though specific team structures aren't detailed in the available information.

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

Şaziye Betül Özateş is an Assistant Professor at Boğaziçi University's Institute for Data Science and Artificial Intelligence, specializing in NLP and machine learning. She develops resources and models for Turkish and low-resource languages, including the BOUN Treebank and dependency parsers. Research focuses on dependency parsing for agglutinative languages, computational linguistics, and deep learning applications, with emphasis on Turkish morphology, code-switching parsing, and historical language processing. Recent projects address Ottoman Turkish NLP and calligraphy analysis. Publications demonstrate strong focus on Turkish language resources (40%), parsing algorithms (30%), historical text processing (20%), and code-switching NLP (10%). Recent works show increasing attention to Ottoman Turkish and Arabic script processing, with methods leveraging multilingual BERT and semi-supervised learning. Developed key resources: BOUN Treebank (Turkish syntactic corpus), PUD Treebank (multilingual parallel corpus), BOUN-Pars (LSTM-based Turkish parser), and semi-supervised parsers for code-switched languages. Supervises projects on neural network applications in NLP.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۴ مورد دیگر

Dr. Mehmet Kayakuş is an Associate Professor at Akdeniz University's Department of Business Information within the Manavgat Faculty of Social and Human Sciences. He holds a PhD in Computer Engineering and has held academic positions since 2010, progressing from Lecturer to Assistant Professor (2018) and Associate Professor (2023). His expertise spans artificial intelligence, machine learning, and data mining applications in communication sciences, finance, and econometrics. He teaches courses in programming (Python, Java, C#), algorithms, and software engineering. Dr. Kayakuş leads 11 national/international research projects and has over 80 publications, including 30+ in SCI journals. His research focuses on AI-driven analyses of corporate reputation, sustainability, and financial metrics. Notable contributions include sentiment analysis systems for tourism, healthcare, and consumer electronics, alongside predictive models for economic indicators and agricultural product quality. His work emphasizes practical applications across diverse sectors—e.g., using ML to forecast tourism revenue shares, model methane gas production, and enhance road lighting efficiency through image processing. He actively collaborates with industry and governmental bodies, contributing to LED conversion projects in street lighting and digital transformation initiatives in banking and e-commerce. Education: BSc in Computer and Control Education, Marmara University (2006) MSc in Computer Electronics, Süleyman Demirel University (2010) PhD in Computer Engineering (2018) Research Highlights: Integrates machine learning with domain-specific challenges—e.g., analyzing social media discourse on EV adoption, predicting phubbing health risks, and optimizing agricultural product deformation energy via non-destructive methods. He also explores sustainability metrics in energy consumption and tourism. Grants/Projects: Leads projects on AI in corporate reputation management, sustainable energy forecasting, and banking digitalization. Collaborates with Turkish Ministry of Health on app-based reputation analysis and European Union carbon emission targets.

Özlem DEFTERLİمشاهده پروفایل

دانشیار

• Fractional Calculus
• Optimal Control Theory
• Mathematical Biology
• +۳ مورد دیگر

Dr. Özlem DEFTERLİ is an Associate Professor in the Department of Mathematics at Çankaya University, Turkey. Her academic career spans over 23 years, with continuous full-time appointments since 2002. She holds a Doctorate in Mathematics (2011) from Middle East Technical University and postdoctoral research experience at Michigan State University and Saginaw Valley State University in the US. Research Focus: Dr. DEFTERLİ specializes in fractional calculus, optimal control theory, mathematical modeling in biological systems, and computational methods. Her work bridges applied mathematics with real-world applications in fields like epidemiology (dengue fever, tumor dynamics), fluid mechanics, and gene-environment networks. Key methods include fractional differential equations, numerical schemes for nonlinear systems, and fuzzy regression models. Recent Contributions: Her 2025 paper explores fractional variational principles in nonlinear oscillators, while 2024 work analyzes pendulum dynamics with time-varying mass. Notable projects include COST Action research on fractional systems and collaborations in transnational disease control via nano-technology. Awards & Recognition: Recipient of the Wen Chen Award (2020) for fractional calculus contributions, TÜBİTAK scholarship (2021), and 20th Anniversary Service Award (2022). She has advised 3 graduate students and holds editorial roles in 24 journals including Chaos, Solitons & Fractals and Fractal and Fractional. Professional Roles: Currently serves on the Faculty Board and Management Committee at Çankaya University. Teaching responsibilities include advanced courses in scientific computation, mathematical modeling, and calculus for business/economics.

Shervin Rahimzadeh Arashlooمشاهده پروفایل

استادیار

• Machine Learning
• Computer Vision
• Kernel Methods
• +۴ مورد دیگر

Shervin Rahimzadeh Arashloo is an Assistant Professor in the Department of Computer Engineering at Bilkent University, Faculty of Engineering. His research focuses on machine learning, kernel methods, anomaly detection, and computer vision applications in fields like face recognition and environmental modeling. He holds a Ph.D. and has extensive academic publications since 2007. His work integrates advanced statistical techniques with real-world challenges, such as hydrological drought modeling, sediment transport prediction, and face spoofing detection. Key contributions include novel one-class classification frameworks, kernel fusion methodologies, and multi-output regression models for environmental systems. Research trends in his publications emphasize robust anomaly detection via kernel-based approaches, optimization of classifier combinations, and application of machine learning to geospatial and biometric security problems. No awards are explicitly mentioned in the provided materials. His lab likely focuses on interdisciplinary projects combining computer science with environmental engineering, though specific lab/team details are not elaborated here.

Erhan Öztopمشاهده پروفایل

استاد

• Computational Neuroscience
• Robotics
• Machine Learning
• +۴ مورد دیگر

Erhan Öztop is a Professor at Özyeğin University's Computer Science Department and Co-Director of the Ozyegin University Robotics Laboratory. He holds a Specially Appointed Professor position at Osaka University's Symbiotic Intelligent Systems Research Center. Previously, he worked at Advanced Telecommunications Research Institute International (ATR) in Japan from 2002-2011, leading as Vice Head of the Communication and Cognitive Cybernetics Department. He earned a Ph.D. in Computer Engineering (2002) from the University of Southern California, M.S. in Computer Engineering (1996) from METU, and B.S. in Computer Engineering + Mathematics (1993) from METU. His research focuses on computational modeling of intelligent behavior, human-robot adaptation, cognitive neuroscience, and machine learning. His work explores visuomotor learning , mirror neuron systems , grasp affordance learning , and human-in-the-loop robot control . Key projects include: Dexterous manipulation via human-robot body schema integration Mental state inference using visual control parameters Motor interference as a metric for human-like robot perception Sign representation of Boolean functions Recent publications emphasize human-robot co-adaptation , emotion modeling , and affordance-based architectures for collaborative systems. His work bridges robotics , cognitive neuroscience , and machine learning to develop biologically inspired intelligent systems.

GÜLTEN ŞEKEROĞLUمشاهده پروفایل

استادیار

• Food Sciences and Engineering
• Food Technologies
• Food Biotechnology
• +۷ مورد دیگر

GültEN ŞEKEROĞLU is an Assistant Professor at Gaziantep University's Naci Topcuoglu Vocational School in the Food Processing Department. She holds a Doctorate, License, and Degree in Food Engineering from Gaziantep University and Ege University. Her educational background includes: Doctorate (2008-2014): Gaziantep University, Faculty of Engineering, Department of Food Engineering Degree (1997-2000): Gaziantep University, Faculty of Engineering, Department of Food Engineering Licence (1988-1994): Ege University, Faculty of Engineering, Food Engineering Department Dr. ŞEKEROĞLU's research focuses on food science and technology with particular emphasis on vegetable oil technology, milk analysis, fat analysis, and chocolate production. Her work bridges fundamental food science with practical applications in the food industry. She has made significant contributions to understanding crystallization behavior of fats, particularly in cocoa butter and milk fat, which directly impacts chocolate quality and shelf life. Her recent research has expanded into sustainable food packaging using agricultural waste materials and the application of artificial intelligence in food industry processes. Her publication record shows a consistent trajectory of high-quality research in food science, with recent publications in Q1 and Q2 journals. Her work spans analytical methods, food packaging development, fat crystallization studies, and oil characterization. She has contributed to both fundamental research on food components and applied studies addressing industry challenges like fat bloom in chocolate and sustainable packaging solutions. Dr. ŞEKEROĞLU has been actively involved in research projects funded by various institutions including TÜBİTAK and the Ministry of Industry. Her eight research projects demonstrate her ability to secure funding and address practical food industry challenges ranging from walnut shell waste utilization to chocolate fat bloom prevention. She has supervised two master's theses on cherry kernel oil properties and chocolate rheology with honey. Her teaching portfolio is extensive, covering 74 courses at the associate degree level and 2 at the undergraduate level, including Vegetable Oil Technology, Milk Product Analysis, and Food Chemistry.

Yusuf Sahillioğluمشاهده پروفایل

استاد

• Computer Graphics
• 3D Shape Processing
• Geometric Algorithms
• +۳ مورد دیگر

Professor Yusuf Sahillioğlu is a faculty member in the Computer Engineering Department at Middle East Technical University (METU), Faculty of Engineering, specializing in computer graphics and geometric processing. His academic journey includes a BS from Bilkent University, MS from University of Florida, and PhD from Koç University, followed by postdoctoral work at Koç University and University of Pennsylvania. His research focuses on 3D shape correspondence , deformation algorithms , deep learning for 3D data , and geometry processing . Key contributions include novel methods for isometric shape matching, topologically-stable correspondence, and real-time secondary animation. His recent work integrates deep learning with traditional geometric approaches for mesh segmentation, point cloud classification, and 3D scene extrapolation. His 15 most recent publications (2021-2025) reveal a strong trend toward real-time geometric algorithms (e.g., spring-decomposed skinning), kernel computation for mesh processing, and deep generative models for 2D-to-3D conversion. The research consistently bridges theoretical geometry with practical applications in animation, reconstruction, and medical imaging. Award highlights include: METU Academic Performance Award (2018) METU Young Scientist Awards (2015-2017) TÜBİTAK 1001 Grants (2016, 2020, 2024) for 3D content analysis, shape matching, and reconstruction TÜBİTAK 3501 Career Grant (2015) for virtual medicine applications He teaches core courses including Data Structures, Operating Systems, Computer Graphics, and Advanced Digital Geometry Processing. His lab focuses on geometric algorithms with applications in medical imaging, animation, and 3D printing, maintaining strong industry and international collaborations through projects like TÜBİTAK-funded initiatives.

• Artificial Intelligence
• Large Language Models
• Computer Vision
• +۷ مورد دیگر

Şener Özönder is a Full-time Associate Professor at Bogazici University, leading the Özönder Lab. His research focuses on AI agents, large language models, computer vision, and AI applications in drug discovery, materials science, and industrial cost prediction. He oversees a computing infrastructure with two 4U GPU servers (6 NVIDIA RTX 4090 GPUs) and a NAS storage system. His research interests include AI-accelerated drug discovery, nanomaterials design via AI/quantum mechanics, and on-device AI agents for real-time API interactions. Key projects include an AI-based drug discovery platform (TÜBİTAK-funded), EU-funded EUPilot for AI accelerator chips, and cloud-based battery monitoring systems (BatteLLIGENCE). Özönder advises four MS students on topics such as LLM agents and cost prediction from engineering drawings. His work bridges physics-inspired AI models with computational quantum mechanics, reflecting his background in both theoretical physics and modern AI applications. Recent projects span nano-material discovery (TÜBİTAK 3501), automotive cost estimation (TÜBİTAK 1711), and vulnerability analysis in post-quantum cryptography (TÜBİTAK BİLGEM). His articles explore AI-driven materials discovery, quantum dot design, and high-energy physics phenomena like gluon saturation and azimuthal correlations in collider experiments. The lab’s infrastructure supports large-scale simulations and machine learning workloads, with a focus on interdisciplinary innovation.

• Computer Vision
• Deep Learning
• Biomedical Engineering
• +۴ مورد دیگر

Vito Paolo Pastore is an Assistant Professor at the University of Genoa's Department of Informatics (DIBRIS), affiliated with the MaLGa research center. His research focuses on interdisciplinary applications of computer vision and deep learning in biomedical engineering, ecology, and transportation systems. Key areas include plankton analysis, medical imaging, neural network dynamics, and autonomous vehicle modeling. Publications span topics like AI-driven medical diagnostics, transfer learning optimization, and ecological monitoring. He has co-developed tools such as SpiCoDyn for analyzing neuronal networks and AGAMAS for traffic simulation. His work bridges computer science with practical applications in healthcare, environmental science, and smart infrastructure. Recent articles highlight contributions to chest radiography AI, plankton classification, and building facade defect detection. Collaborations span institutions like the University of Genoa and international research groups.

• Computer Architecture
• Multi-core Systems
• Fault-Tolerant Computing
• +۴ مورد دیگر

Dr. Işıl Öz is an Assistant Professor in the Computer Engineering Department at Izmir Institute of Technology (IZTECH). She holds a B.Sc. and M.Sc. in Computer Engineering from Marmara University and a Ph.D. from Boğaziçi University. Before joining IZTECH in 2018, she worked as a postdoctoral researcher and ERCIM/Marie Curie Fellow at the Swedish Institute of Computer Science (SICS). Her research focuses on computer architecture, performance optimization, and reliability of multi-core systems, with a strong emphasis on fault-tolerant computing and GPGPU applications. Key projects include the TÜBİTAK-funded FTGPGPU initiative analyzing hardware fault tolerance for GPU applications. She teaches courses such as Operating Systems, Advanced Computer Architecture, and Parallel Programming Patterns. Her work spans machine learning-based vulnerability prediction, compiler design for reliable execution, and approximation techniques for efficient parallel computing. Publications appear in venues like ACM Computing Surveys, The Journal of Supercomputing, and International Journal of Parallel Programming. Awards: ERCIM/Marie Curie Fellowship Labs/Teams: Parsiyte Research Group (focused on parallel and distributed systems) Grants: TÜBİTAK ARDEB 3501 (FTGPGPU project)

MUHARREM ERGUNمشاهده پروفایل

استاد

• Postharvest Physiology
• Horticultural Science
• Plant Physiology
• +۵ مورد دیگر

Prof. MUHARREM ERGUN is a Professor in the Department of Horticultural Sciences at Bingöl Üniversitesi, Turkey. He previously held academic positions at Kahramanmaraş Sütçü İmam Üniversitesi and has been part of the faculty at Bingöl since 2010. His academic journey includes a PhD from the University of Florida, USA (2003), with prior degrees from Ege Üniversitesi and Orta Doğu Teknik Üniversitesi. His research focuses on postharvest physiology, plant quality preservation, and horticultural innovations. Notable areas include ethylene inhibition techniques using 1-MCP, walnut genotype analysis, and functional food studies. He has authored over 35 international journal articles and contributed chapters to books on topics like fresh-cut produce technology and sustainable agriculture. His work frequently addresses challenges in vegetable and fruit storage, quality enhancement, and genetic diversity. Ergun has supervised 8 PhD/Master’s theses, including studies on walnut selection, carrot preservation, and cucumber quality. He has led or participated in research projects such as the 'Integrated Project to Develop Walnut Cultivation in Turkey' (TÜBİTAK, 2008–2012). His international collaborations include studies at the University of Nebraska and BOKU Wien. Awards include a YOK Fellowship (2013) and TÜBİTAK-funded research (2008). He has published 10+ books/monographs, including contributions to seminal texts like Taze Kesilmiş Ürün Teknolojisi and Genel Sebzecilik . His current research interests span innovative horticultural practices, phytochemical analysis, and sustainable food systems.

• Mathematical Modeling
• Optimal Control
• Infectious Diseases Dynamics
• +۴ مورد دیگر

Tuğba Akman is an Associate Professor in the Department of Computer Engineering. Her research focuses on mathematical modeling and optimal control of complex biological systems, with particular emphasis on infectious diseases, cancer dynamics, and fractional-order calculus applications.

Atakan Altınkaynakمشاهده پروفایل

دانشیار

• Additive Manufacturing
• Finite Element Analysis
• Mechanical Engineering
• +۳ مورد دیگر

Atakan Altınkaynak is an Associate Professor in the Department of Mechanical Engineering at Istanbul Technical University (ITU), affiliated with the College of Engineering. His research focuses on additive manufacturing, finite element analysis, polymer processing, and vibration analysis. Key areas include Fused Deposition Modeling (FDM), fluid-structure interaction, and origami-inspired mechanical systems. Research Interests: Additive Manufacturing (3D Printing Technologies) Finite Element Analysis and Numerical Methods Mechanical Vibration and Dynamic Systems Polymers Extrusion and Material Processing Fluid-Structure Interaction Modeling Awards: Doctoral Finishing Fellowship (2010) İTÜ Bitirme Tasarım Projesi Birincilik Ödülü (2016) Lew Erwin Memorial Scholarship (2007) Advising/Grants: Supervised 23 research works and led 8 projects including: "FDM Yazıcılarda Çoklu Şerit Basımının Sayısal Analizi" (2023-2024) "Polimer-Metal Temas Yüzeylerinde Sürtünme Kaynaklı Gürültünün Sayısal Modellenmesi" (2018-2019) "Filament Beslemeli 3 Boyutlu Yazıcıların Performans Karakteristiğinin Belirlenmesi" (2017-2019) His work bridges computational modeling with experimental validation in advanced manufacturing and mechanical systems.