جست‌وجوی استاد و پژوهشگر

Baran Toprakمشاهده پروفایل

استادیار

• Geotechnical Engineering
• Foundation Engineering
• Soil Mechanics
• +۲ مورد دیگر

Baran Toprak serves as an Assistant Professor in the Geotechnics Department within the Department of Civil Engineering at Kırıkkale University's Faculty of Engineering and Natural Sciences. Appointed to this faculty position in February 2020 following completion of his doctorate, he has been affiliated with the university since 2002 after military service completion in 2001. His academic credentials include: Civil Engineering degree from Balıkesir University Faculty of Engineering and Architecture (1999) Master's in Geotechnics (2005) Doctorate (2019) Dr. Toprak's research centers on Geotechnical Engineering with specialized expertise in foundation design under dynamic loads, soil-structure interaction, and innovative soil improvement techniques. His work addresses critical challenges in low-bearing-capacity soils through methods like fly ash column treatment and advanced in-situ testing (CPT/SPT). He investigates seismic behavior of reinforced concrete structures on improved soils and develops protective systems like gabion walls for blast mitigation, bridging theoretical analysis with practical field applications across earthquake-prone regions of Turkey. Analysis of his 15 publications (2013-2025) reveals consistent focus on geotechnical investigation methodologies, foundation engineering in challenging soils, and dynamic soil-structure interaction. Key trends include utilization of industrial byproducts (fly ash, slag) for soil stabilization, optimization of structural systems via metaheuristic algorithms, and detailed post-earthquake damage assessments linking soil amplification to building resonance. His research demonstrates strong field application emphasis through municipal projects in Kırıkkale and Düzce provinces. No scientific awards were documented in the source materials. No information regarding student advising, research grants, or laboratory leadership was provided in the available documentation.

• Operations Research
• Multiple Criteria Decision Making
• Data Envelopment Analysis
• +۱ مورد دیگر

Dr. Muhammed Maruf is an Assistant Professor at the Faculty of Economics and Administrative Sciences , Kırşehir Ahi Evran University since 2019, with prior roles at Şırnak University (2017-2019) and Dokuz Eylül University (2011-2017). He holds a PhD in Business Administration (2013-2017) and an MSc in Management Science (2011-2013) from Dokuz Eylül University, and a BSc in Business Administration (2002-2005) from Erciyes University. Licenses : YÖKDİL (2017, 82), ÜDS (2011, 71) Administrative Roles : Research Application Center Director (2019-), Deputy Department Head (2019-), Head of Department (2018-), Dean Assistant (2018-), Faculty Council Member (2017-) His research focuses on Operations Research and Multiple Criteria Decision Making , applying advanced methods like CRITIC , MAIRCA , DEA , and Fuzzy Logic to analyze performance in municipal governance, tourism websites, banking transformation, and political participation. Collaborative work spans 13 co-authors, notably with Kadir Özdemir (6 publications) and Bekir Gündoğmuş (5 publications). Key Trends : 15+ journal articles (2021-2025), 4 books, 4 book chapters Methodological Expertise : CRITIC-MAIRCA integration, Fuzzy DEA, Grey System Theory Project Leadership : 2 projects (2020-2021, 2022-2024), 2 as co-researcher Academic Impact : Google Scholar h-index 8 (157 citations), YÖKSİS h-index 6 (365 total points). His 43+ total publications include 28 journal articles and 9 conference proceedings.

• Earthquake Engineering
• Concrete Structures
• Steel Structures
• +۴ مورد دیگر

Prof. METİN HÜSEM is a Professor at Karadeniz Technical University's Faculty of Engineering, Department of Civil Engineering, specializing in structural and earthquake engineering. With a career spanning over three decades, he has held key roles including Dean (2016–2020) and Department Head (2014–2016, 2023–present). His research integrates experimental and computational methods to advance seismic resilience, materials science, and sustainable construction. Education: Doctorate in Civil Engineering, Karadeniz Technical University (1990–1995) Postgraduate in Civil Engineering, Karadeniz Technical University (1986–1990) Undergraduate in Civil Engineering, Karadeniz Technical University (1982–1986) Research Focus: His work targets earthquake-resistant structures, material innovations (geopolymers, fiber-reinforced concrete), and structural health monitoring. Key areas include: Seismic retrofitting of buildings and heritage structures High-temperature effects on concrete Development of energy-dissipating devices (e.g., patented seismic dampers) Optimization of prefabricated and composite systems Publication Trends: Recent articles emphasize post-earthquake damage assessment, geopolymer materials, and cyclic load behavior of structures. A consistent theme is the translation of field data into practical design improvements, particularly for reinforced concrete and masonry systems in seismic zones. Grants & Advising: He has led 13 funded projects (e.g., TUBITAK-supported studies on masonry walls and seismic dampers) and advised 45+ graduate students. His patents include innovations like modular energy dissipators and interlocked masonry systems. Laboratory & Teams: Manages advanced structural testing facilities, collaborating with national/international researchers on earthquake simulations and material durability experiments.

ŞERİF ÖZLÜمشاهده پروفایل

دانشیار

• Fuzzy Logic
• Decision Support Systems
• Neutrosophic Sets
• +۴ مورد دیگر

ŞERİF ÖZLÜ is an Associate Professor at Gaziantep University , currently affiliated with the Nizip Vocational School in the Department of Food Processing . He previously served as a Doctor Teaching Staff member at the same institution. Education PhD in Mathematics , Nevşehir Hacı Bektaş Veli University (2011-2015) MSc in Mathematics , Gaziantep University (2009-2011) BSc in Mathematics , Afyon Kocatepe University (2004-2008) Research Interests Özlü’s work focuses on advanced fuzzy logic frameworks, including Bipolar-Valued Type-2 Fuzzy Sets , Neutrosophic Operational Research , and Soft Set Theory . His research integrates these concepts into Multi-Criteria Decision Making (MCDM) problems, with applications in engineering, business, and technology. Key methodologies include aggregation operators (Dombi, Choquet), similarity measures (Dice, Cosine), and hybrid systems combining fuzzy logic with probabilistic or temporal models. Publication Trends Özlü has published extensively in 2024-2025 on cutting-edge fuzzy logic extensions like probabilistic hesitant fuzzy sets and q-rung orthopair models . Earlier works (2014-2021) explored foundational topics in soft set theory, neutrosophic sets, and their algebraic properties.

Mustafa Özuysalمشاهده پروفایل

استادیار

• Computer Vision
• Object Detection
• Object Tracking
• +۵ مورد دیگر

Mustafa Özuysal is an Assistant Professor in the Department of Computer Engineering at the College of Engineering, Izmir Institute of Technology (İYTE), where he leads the Visual Intelligence Research Group. His research focuses on computer vision, including object detection, tracking-by-detection, and real-time scene text recognition, with applications on mobile devices. Research Interests: Large-scale object detection Object detection and tracking on mobile platforms Real-time scene text recognition Feature learning from image and video sequences Augmented reality and camera egomotion estimation His scholarly work includes influential publications in IEEE TPAMI, IET Computer Vision, and top-tier conferences such as CVPR and ECCV, particularly in local feature descriptors like BRIEF and keypoint recognition using random ferns. His research emphasizes efficient, real-time algorithms suitable for embedded and mobile systems. Scientific Contributions: Co-developer of the BRIEF descriptor, widely used in computer vision for fast binary feature matching. Contributor to tracking-by-detection frameworks and homography estimation methods robust to occlusions and viewpoint changes. Dr. Özuysal has taught a range of undergraduate and graduate courses, including Introduction to Image Understanding, Vision-Based Tracking and Modeling, Data Structures, and Mobile Application Development. He advises the Visual Intelligence Research Group and continues to advance research in scalable and efficient vision systems.

• Financial Markets
• Mathematical Finance
• Derivatives
• +۶ مورد دیگر

Vedat Akgiray is a Professor at Bogazici University, holding a Ph.D. from Syracuse University. His teaching and research areas focus on Derivatives , Portfolio Management , Probability , and Financial Markets , with a particular emphasis on Mathematical Finance . He has published extensively on topics such as FinTech, corporate governance, pension systems, and risk management. Education : Ph.D., Syracuse University Email: akgirayv@bogazici.edu.tr

Selin Aslanمشاهده پروفایل

استادیار

• Applied Mathematics
• Computational Mathematics
• Imaging Science
• +۲ مورد دیگر

Selin Aslan serves as an Assistant Professor in the Department of Mathematics at Koç University, Istanbul, Turkey, where she conducts research at the intersection of computational mathematics and imaging science. Her academic appointments and research activities are centered within the university's mathematics department, contributing to both undergraduate and graduate education in mathematical sciences. Her educational qualifications include: PhD in Mathematics from Virginia Polytechnic Institute and State University (2018) Master's in Mathematics from Rochester Institute of Technology (2013) B.A. in Mathematics from Ege University (2010) Dr. Aslan's research program focuses on developing advanced computational methods for solving inverse problems in imaging, with particular expertise in phase retrieval, tomographic reconstruction, and ptychography. Her work bridges theoretical mathematics with practical applications in medical imaging, microscopy, and materials science, emphasizing algorithmic innovation and computational efficiency. She integrates techniques from deep learning, optimization theory, and high-performance computing to address challenges in image reconstruction under physical constraints. Analysis of her publication record reveals a consistent trajectory toward solving complex imaging problems through hybrid approaches that combine physics-based models with data-driven techniques. Her recent work demonstrates increasing emphasis on scalability for large datasets, robustness in photon-limited scenarios, and real-time processing capabilities, with applications spanning biomedical imaging to advanced microscopy. No scientific awards were documented in the available sources. Information regarding student advising and research grant activities was not specified in the provided materials, though her publication record suggests active research collaboration. Her computational focus implies engagement with high-performance computing resources for large-scale image reconstruction tasks. While specific laboratory infrastructure details were unavailable, her research on multi-GPU implementations and distributed computing indicates utilization of advanced computational facilities for handling large-scale imaging datasets.

Tolga Ovatmanمشاهده پروفایل

استاد

• Algorithms and Computing Theory
• Computer Software and Software Engineering
• Cloud Computing
• +۶ مورد دیگر

Prof. Dr. Tolga Ovatman is a faculty member at the Department of Computer Engineering, Istanbul Technical University , where he has been serving as Head of Department since 2024. His academic career spans roles from Research Assistant (2004-2012) to Associate Professor (2019-2023) and full Professor (2023-present). He previously held administrative roles such as Vice Dean (2018-2022) and Deputy Head of Department (2016-2018). PhD in Computer Engineering (2005-2011) MS in Computer Engineering (2003-2005) BSc from Hacettepe University (1999-2003) His research focuses on model checking , replicated state machines , cloud computing , and object-oriented software . Recent work addresses computation offloading in 6G networks , collaborative text editing data structures , and energy-efficient environmental monitoring systems . Key projects led include Design of a Multiplexed State Machine Storage System for Edge Computing (2022-2024) and Microservice Compatible Symphony Infrastructure Research (2020). He has supervised numerous theses on topics ranging from collaborative text editing to AI applications in watershed management . Publications span IEEE Transactions , Springer , and conferences like CSCE and CLOSER .

Serdar ARSLANمشاهده پروفایل

مدرس

• Database Management Systems
• Data Structures and Algorithms
• Machine Learning
• +۳ مورد دیگر

Dr. Serdar Arslan is a Lecturer at the Department of Computer Engineering at Cankaya University. He holds a PhD in Computer Engineering from Middle East Technical University (METU), with a thesis on multidimensional data indexing. His academic background includes a Master's (2005) and Bachelor's (2001) in Computer Engineering from METU and Hacettepe University, respectively. His research focuses on database systems, machine learning, multimedia data indexing, and forecasting models. Education: Bachelor of Engineering, Computer Engineering, Hacettepe University (2001) Master of Science, Computer Engineering, METU (2005) Doctor of Philosophy, Computer Engineering, METU (2018) Research Interests: Machine Learning applications in healthcare forecasting and financial markets Advanced indexing techniques for multimedia databases (e.g., MM-FOOD structure) Natural language processing for stance detection in political discourse Hybrid forecasting models combining LSTM and Prophet algorithms Domain-specific NLP for product name extraction in Turkish text Publications: His recent work emphasizes machine learning-driven solutions for complex systems, including pandemic modeling, cryptocurrency analysis, and conflict discourse analysis. His earlier contributions focused on multimedia indexing and image retrieval systems using MPEG-7 standards. The 2025 paper on OSINT architecture frameworks highlights his expanding focus on cybersecurity and system design. Labs/Teams: While no specific lab is mentioned, his GitHub repositories (e.g., Forecasting, NLP projects) suggest active involvement in collaborative research projects related to his domains.

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

Mustafa Taha Koçyiğit serves as an Assistant Professor at Boğaziçi University, specializing in artificial intelligence and computer vision research. His academic role focuses on advancing deep learning methodologies within the university's engineering or computer science framework. His research interests encompass deep learning, self-supervised learning, efficient training of deep learning and large language models, computer vision, and language-grounded vision systems. He develops computationally and data-efficient techniques to enhance AI model training and deployment across diverse applications. Analysis of his 2020-2025 publications reveals consistent emphasis on training efficiency: accelerating self-supervised learning, optimizing computer vision methods, and applying deep learning to industrial defect detection. His work bridges theoretical advancements with practical aerospace and manufacturing solutions. No scientific awards are documented in the source material. Information regarding student advising, grant funding, laboratory facilities, or research teams remains unavailable.

• High-Energy Physics
• Particle Physics
• Proton-Proton Collisions
• +۵ مورد دیگر

Muammer Altan Çakır is a Professor in the Department of Physics Engineering at Istanbul Technical University, actively engaged in high-energy physics research with significant contributions to the CMS Collaboration at CERN. His work focuses on proton-proton collisions, Higgs boson physics, and top quark studies using Large Hadron Collider data. His research interests span experimental particle physics with emphasis on proton-proton collisions , Higgs boson characterization , lepton physics , and transverse momentum analysis . Recent work explores charm baryon production, Drell-Yan processes, and muon identification techniques using advanced multivariate methods in the CMS detector. Analysis of his 15 most recent publications reveals a strong focus on precision measurements in high-energy collisions, particularly in Higgs physics (3 publications), top quark physics (2), and detector optimization (2). His work consistently addresses fundamental questions in the Standard Model through advanced statistical techniques and large-scale data analysis. Doktora sonrası araştırma bursu (2010) Landes Baden Württenberg Doktorarbeit Stipendium (2006) LPC Fall Guest Visitor Faculty (2017) Multiple Performans ödülü awards (2012, 2013, 2015) Professor Çakır has supervised 15 students and leads multiple research projects including GPU-based distributed computing platforms for big data processing, real-time predictive maintenance systems, and deep learning applications for top quark spin correlation studies. His current projects integrate generative AI with domain-specific physics research while developing scalable open-source big data architectures for industrial applications. His laboratory work centers on CMS detector data analysis, with recent focus on online data visualization tools and multivariate techniques for particle identification. Current projects explore GPU-accelerated computing frameworks and generative AI applications for physics-informed design systems.

Meltem Aksoyمشاهده پروفایل

دانشیار

• Sustainable Urban Development
• Social Housing Practices
• User Participation in Design
• +۷ مورد دیگر

Meltem Aksoy is an Associate Professor at the Department of Architecture, Istanbul Technical University. Her academic work spans urbanization processes, social housing practices, and digital design technologies, with a particular focus on user participation and ecological sustainability in the built environment. Current affiliation: Department of Architecture, Istanbul Technical University Research themes: Composite cities, informal settlements, parametric design, ambient intelligence Her research explores: Intersections of digital technologies and spatial perception Methodologies for participatory social housing Computational approaches to architectural decision-making Temporal-spatial dynamics in contemporary urbanization Recent publications demonstrate trends in: AI-assisted design negotiation frameworks Fuzzy logic applications in architectural performance Critical analyses of composite urban structures Evolution of home-street relationships She has supervised 33 graduate theses spanning topics from: Architectural essay films Political space narratives Smart facade technologies Urban data representation

Hande Demirelمشاهده پروفایل

استاد

• GIS
• Remote Sensing
• Photogrammetry
• +۷ مورد دیگر

Prof. Hande Demirel is a Professor at the Department of Geomatics Engineering, Istanbul Technical University. She holds a PhD in Geoinformatics from Technical University of Berlin (2002). Her academic career includes roles as Associate Professor (2008–2019) and Assistant Professor (2004–2008) at ITU, alongside research at the European Commission Joint Research Center (2011–2014). She specializes in GIS applications, remote sensing, photogrammetry, and spatial data analysis. Education: B.Sc. (1996) and M.Sc. (1998) in Geodesy & Photogrammetry from ITU, followed by a PhD in Geoinformatics (2002) from TU Berlin. Awards include Best PhD Award (2003), DAAD Scholarship (2007), and Best Poster Award (2016). Research focuses on transportation accessibility, climate change impacts, 3D spatial modeling, and BIM-GIS integration. She leads projects like 'Building Information Model Based Fire Evacuation Simulation' (TUBITAK-funded) and 'Spatio-Temporal Accessibility Analysis in Istanbul'. Key contributions include over 30 peer-reviewed publications, including works on land use prediction, ship detection via AI, and indoor navigation systems. She advises numerous graduate students, with 15+ theses supervised since 2009. Active in professional societies including the German and American Associations for Remote Sensing.

Marcel Garzمشاهده پروفایل

دانشیار

• Media Studies
• Political Science
• Economics
• +۷ مورد دیگر

Marcel Garz is an Associate Professor at Jönköping International Business School, part of Jönköping University in Sweden. His research bridges economics, communication studies, and political science, focusing on digital technologies' impact on media, politics, and human behavior. He specializes in causal inference methods and computational tools like deep learning and computer vision. Current projects include leading the Global Social Media Experiment (a Nordic cross-cultural study on social media effects) and organizing the Data Methods Initiative (a seminar series promoting computational methods in social science). He co-founded the Economics of Media Bias Workshop and collaborates with institutions like the Swedish Competition Authority on media quality research. Research interests emphasize algorithmic curation's societal effects, media bias, and public policy. His work spans topics like news quality under market competition, pandemic behavior modulation via media, and tax enforcement through data transparency. Key contributions include frameworks on unethical marketing manipulation, signaling theory in crowdfunding, and the role of media coverage in electoral outcomes. He has published widely in journals like Journal of Communication , Political Behavior , and Journal of Economic Behavior & Organization . Funding: A three-year grant from the Swedish Competition Authority (2023–2025) supports research on media competition and news quality.

Orhan Ecemişمشاهده پروفایل

دانشیار

• Quantitative Decision Methods
• Multi-Criteria Decision Making
• Data Analytics
• +۴ مورد دیگر

Orhan Ecemiş serves as an Associate Professor at Gaziantep University's Technical Sciences Vocational School within the Electronics and Automation Department, specializing in Robotics and Artificial Intelligence. His academic appointment commenced in 2024 following progression from Doctor Lecturer (2022-2024) and Lecturer (2009-2022) positions. He currently holds administrative roles as Head of Department and Deputy Director of Vocational School/College at Gaziantep University, having previously served in these capacities during 2010-2014 and 2020-2022. His educational background includes a Doctorate in Econometrics from Akdeniz University (2011-2016), a Master's in Computer Education from Gazi University (2001-2004), and undergraduate studies in Computer Teaching at Gazi University (1996-2000). Ecemiş specializes in Quantitative Decision Methods, Multi-Criteria Decision Making, Data Analytics, and Operations Research, with significant contributions to Artificial Intelligence applications. His research bridges computer science and economic modeling, focusing on practical decision support systems across diverse domains including energy policy, logistics optimization, and digital transformation. His work consistently applies advanced mathematical frameworks to real-world problems, particularly utilizing neutrosophic logic and machine learning techniques for complex decision environments. His 15 most recent publications demonstrate strong thematic continuity in applying Multi-Criteria Decision Making methods to contemporary challenges, with increasing focus on sustainability metrics, digital technologies, and economic forecasting. The research spans energy policy evaluation, cloud computing selection, green logistics, and international trade analysis, reflecting both methodological sophistication and practical relevance to Turkish and European contexts. As an academic supervisor, he has guided at least one Master's thesis to completion in 2025. His teaching portfolio encompasses computer programming, web technologies, algorithms, and data science applications across undergraduate and associate degree programs since 2014. While specific grant information isn't detailed in the source material, his extensive publication record across international journals and conference proceedings indicates substantial research activity.