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.

• Artificial Intelligence
• Robotics
• Deep Learning
• +۵ مورد دیگر

Ozgur S. Oguz is an Assistant Professor at Bilkent University , Faculty of Computer Engineering, and the lead of the Learning for Intelligent Robotic Agents (LiRA) Lab . His research focuses on enhancing autonomous agents' capabilities in learning, reasoning, and planning, particularly for robotics applications. Education : PhD in Computer Science from TU Munich , studies at University of British Columbia (UBC) and Koç University , postdoctoral work at University of Stuttgart and Max Planck Institute for Intelligent Systems . His research explores algorithms for autonomous decision-making, with emphasis on deep learning , reinforcement learning , and robotics . Recent work includes diffusion-based reinforcement learning , hindsight experience prioritization , and hybrid manipulation planning , often addressing challenges in sequential task execution and tactile-based control. Key trends in his publications revolve around robotic manipulation , motion planning , and human-robot interaction . He has contributed to conferences like NeurIPS , ICRA , IROS , and journals such as IEEE TRO and Scientific Reports .

• Earth Physics
• Applied Geophysics
• Paleomagnetism
• +۳ مورد دیگر

Prof. Turgay İşseven is a Professor at the Department of Geophysical Engineering, Faculty of Mining, Istanbul Technical University. He holds a PhD in Geophysical Engineering from the same institution. His primary research interests include Earth Physics, Applied Geophysics, and Paleomagnetism, with a focus on tectonic evolution, volcanic rock analysis, and gravity modeling in regions like Eastern Anatolia and Thrace Basin. He has led multiple projects funded by TÜBİTAK and BAP, investigating topics such as the paleomagnetic properties of volcanic rocks and the structural analysis of sedimentary basins. Prof. İşseven has advised numerous graduate students and contributed to over 20 publications in peer-reviewed journals. His work integrates advanced geophysical techniques like Ground Penetrating Radar (GPR) and deep learning for subsurface imaging and object detection. Key projects include the investigation of Lake Van's volcanic formations and the development of software for gravity data processing. He is also involved in teaching courses on Geomagnetism and Paleomagnetism. Educational Background: PhD in Geophysical Engineering, Istanbul Technical University (2001) MSc in Geophysical Engineering, Istanbul Technical University (1995) BSc in Geophysical Engineering, Istanbul Technical University (1991) Research Interests: Gravity anomalies and structural modeling Paleomagnetic studies of volcanic rocks Geophysical exploration techniques (GPR, resistivity) Tectonic evolution of Anatolia and the Eastern Mediterranean Projects: Investigation of Miocene-Quaternary volcanic rocks in Lake Van using paleomagnetic methods Gravity modeling of sedimentary basins in Eastern Anatolia Development of GravPack, a MATLAB-based gravity data processing tool Advising and Labs: Advisor to 7+ graduate students (e.g., Nedim Aydın, Orhan Apaydın) Collaborations with institutions like the Eurasian Geosciences Institute His research contributes to UN Sustainable Development Goals related to climate action and sustainable cities, through studies on earthquake hazard mitigation and geological resource management.

Orhan Akyılmazمشاهده پروفایل

استاد

• Geodesy
• Satellite Gravity Missions
• Water Resource Monitoring
• +۵ مورد دیگر

Orhan Akyılmaz serves as a Professor in the Department of Geomatics Engineering at Istanbul Technical University, Turkey, with continuous research activity since 2004. His work bridges geodetic science with environmental monitoring through satellite gravity missions and advanced computational methods. His research focuses on satellite gravity field modeling (GRACE/GRACE-FO missions), machine learning applications for hydrological monitoring, and geodetic algorithm development . Key contributions include deep learning-aided temporal downscaling of water storage data, high-resolution gravity field products, and optimized topographic correction algorithms using digital elevation models. His fingerprint reveals strong expertise in Fuzzy Inference Systems (100%), Earth Rotation Parameters (72%), and Quaternion-based transformations (66%). Recent publications (2022-2024) demonstrate a pronounced trend toward integrating deep learning with satellite geodesy to address water resource challenges, particularly in groundwater monitoring and gap-filling between satellite missions. His work consistently targets practical environmental applications while advancing computational geodesy. Scientific recognition includes: TUJK Bilim Ödülü (Science Award) from the Turkish National Union of Chambers of Survey Engineers (2011) He secured TÜBİTAK funding (2020-2023) for the project "Grace ve Çoklu-Görev Uydu Uzaktan Algılama Verileri ile Yüksek Çözünürlüklü Yeraltı Su Bütçesi İzleme Sistemi" (High-Resolution Underground Water Budget Monitoring System). His supervised work encompasses 8 students, though specific names aren't provided in source materials.

• Artificial Intelligence
• Robotics
• Reinforcement Learning
• +۳ مورد دیگر

Ozgur S. Oguz is an Assistant Professor in the Department of Computer Engineering at Bilkent University, leading the Learning for Intelligent Robotic Agents (LiRA) Lab. His research focuses on developing algorithms for autonomous agents, emphasizing learning, reasoning, and planning capabilities in robotics and decision-making domains. Prior to joining Bilkent, he was a postdoctoral researcher at the Max Planck Institute for Intelligent Systems and Stuttgart University, and earned his PhD from TU Munich in Human-Robot Interaction (HRI). He holds degrees from UBC and Koç University. His research interests span AI, robotics, reinforcement learning, and robotic manipulation planning. Notable contributions include work on curriculum-based reinforcement learning, safe learning frameworks for dynamical systems, and hybrid planning algorithms for sequential manipulation tasks. He actively teaches courses such as Learning for Robotics (CS 449/549) and Artificial Intelligence (CS 461). Recent publications highlight advancements in diffusion-based curriculum learning, corrected experience replay methods, and neural field representations for articulated object manipulation. His work frequently appears in top venues like NeurIPS, ICRA, and IROS. He mentors graduate and undergraduate students in AI and robotics, with current opportunities for postdoctoral researchers. Key collaborations include projects with the Cluster of Excellence IntCDC and the LiRA Lab’s focus on interdisciplinary robotics research.

Muhammed Kotanمشاهده پروفایل

استادیار

• Artificial Intelligence
• Computer Software
• Image Processing
• +۱۳ مورد دیگر

Muhammed Kotan is an Assistant Professor at the Department of Information Systems Engineering , Sakarya University , where he has served since 2022. His academic career includes roles as a Research Assistant (2011–2022) at Sakarya University and Afyon Kocatepe University. He holds a PhD in Computer and Information Engineering (2020), an MSc in Computer and Information Engineering (2014), and a BSc in Computer Engineering (2011) from Sakarya University. Research Interests : Artificial Intelligence, Computer Software, Image Processing, Machine Learning, Computer Vision, Medical Imaging, Energy Efficiency Optimization, Natural Language Processing, Sentiment Analysis, Feature Selection, 3D Reconstruction, Industrial Machine Detection, Optimization Algorithms, Real-Time Systems, User Reviews Analysis, E-Commerce Analytics. Key Contributions : Developed hybrid methods for 3D reconstruction and industrial machine defect detection, optimized tow train routing in manufacturing, and applied Marine Predators Algorithm for mental health screening. Scientific Recognition : Awarded the Eğitim Öğretimde Üstün Başarı Ödülü by Sakarya University (2024). Served as editor for the Sakarya University Journal of Computer and Information Sciences (2023–2024) and peer reviewer for journals like Signal, Image and Video Processing and Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi . Advising : Co-advisor for TÜBİTAK projects (2022–2024) and supervised student research on topics like cosmetic product recognition, natural language processing, and sentiment analysis. Designed courses in Digital Image Processing, Text Mining, and Advanced Information Systems.

• Interior Architecture Education
• Digital Technologies in Interior Design
• Disaster Management in Interior Spaces
• +۴ مورد دیگر

Assoc. Prof. Dr. Orkan Zeynel Güzelci is an academic at Istanbul Technical University's Faculty of Architecture, leading the Interior Architecture Department. His roles include Department Vice Chair (2023–present) and Associate Professor since 2023. He holds a post-doctorate from the University of Porto's Faculty of Architecture (2020–2021) and a PhD from Istanbul Technical University (2012–2018). His research focuses on computational design education, disaster-resilient interior spaces, and traditional architectural forms' digital reinterpretation. Education: Post-Doctorate: University of Porto, Faculty of Architecture (2020–2021) PhD: Istanbul Technical University, Architectural Design (2012–2018) MSc: Istanbul Technical University, Architectural Design (2010–2012) Bachelor's: Istanbul Kültür University, Architecture (2006–2010) Research Interests: Integrating AI and generative algorithms into architectural education Disaster management in interior environments Historical architectural patterns' computational analysis 3D printing and digital fabrication in design Recent Research Trends: Prof. Güzelci's work emphasizes bridging traditional architectural knowledge with modern computational tools. Recent studies explore AI-driven design solutions, sustainable materials, and heritage preservation through machine learning models. His projects often combine theoretical frameworks with practical applications, such as predictive models for historical mosque elements and risk-reduction strategies for residential interiors. Awards & Recognition: 2017: 1st Prize in Aegean Region Urban Design Competition 2013: 1st Prize in Bursa Urban Design Competition 2021: EDU-AI pedagogical innovation award Advising & Grants: Prof. Güzelci has supervised numerous design studios and research projects. His grants include funding for computational design education initiatives and disaster-resilient interior design frameworks. He actively participates in international conferences and serves as a jury member for architectural competitions. Lab & Teams: Leads the Computational Design Research Group at Istanbul Technical University, focusing on AI applications in design education and heritage conservation.

• Algorithms and Data Structures
• Big Data
• High Performance Computing
• +۷ مورد دیگر

Francesco Silvestri is an Associate Professor in Computer Engineering at the Department of Information Engineering, University of Padova. Previously, he held roles including Assistant Professor (2016-2019) and post-doctoral positions at the University of Padova and IT University of Copenhagen. He also served as a part-time lecturer at IT University of Copenhagen (2013-2014) and as a visiting scholar at the University of Texas at Austin (2006-2007). He earned his Ph.D. in Computer Engineering from the University of Padova in 2009. His research focuses on algorithms and data structures, emphasizing big data efficiency, high performance computing, and modern architectures. Key areas include similarity search, dimensionality reduction, graph mining, and parallel algorithms. He supervises PhD students and collaborates with researchers globally. His work has been recognized with awards such as the ICDT Best Paper Award (2023) and the ACM SIGMOD Research Highlights Award (2020). Teaching includes courses like Big Data Computing and Algorithm Design at the University of Padova and IT University of Copenhagen. He has served on program committees for major conferences like Euro-Par, IPDPS, and SIGMOD. His contributions span academic publications and industrial collaborations, including work on mobility data analysis and resilient algorithms. He is affiliated with the AIDA Lab (Algorithms for Intelligent Data Analytics) and actively contributes to the academic community through editorial roles, such as being an Associated Editor of the ACM Transactions on Parallel Computing.

• Remote Sensing
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Şaziye Özge Atik is an Assistant Professor at the Department of Geomatics Engineering, Faculty of Civil Engineering, Istanbul Technical University. Her research focuses on Remote Sensing and Computer Vision, with applications in machine learning, hyperspectral imaging, and urban remote sensing. She holds a PhD in Geomatics Engineering from Istanbul Technical University (2021) and has held academic positions including Doctorate Lecturer (2023–present) and Lecturer roles at Gebze Technical University (2020–2023). She was an Academic Visitor at Twente University’s ITC EOS Department in 2018. Her academic achievements include winning the IEEE GRSS Türkiye Best Thesis Competition (2022). She has published extensively on topics such as satellite imagery analysis, UAV-based geospatial technologies, and machine learning applications in remote sensing. Her work integrates deep learning, object-based image analysis, and geospatial data processing to address environmental and urban challenges. Research interests span spectral-spatial data fusion, optimal band selection in hyperspectral imaging, and automated cartographic generalization. She has contributed to projects on coastal zone management, urban vegetation classification, and emergency evacuation modeling using geospatial algorithms like Dijkstra’s pathfinding.

• Applied Geophysics
• Geophysical Engineering
• Non-Destructive Testing
• +۴ مورد دیگر

Orhan Apaydın is a Researcher at the Department of Geophysical Engineering, Istanbul Technical University. He holds a PhD in Geophysical Engineering (2023), an MSc with Thesis in Geophysical Engineering (2020), and a BSc in Geophysical Engineering (2014). His research focuses on applied geophysics, particularly Ground Penetrating Radar (GPR), non-destructive testing, and deep learning applications in geophysical imaging. He has contributed to studies on reinforced concrete structure analysis, buried object detection using AI models like Faster R-CNN and YOLOv5, and portable measurement systems for through-obstacle imaging. Education: PhD in Geophysical Engineering (2023), Istanbul Technical University MSc in Geophysical Engineering (2020), Istanbul Technical University BSc in Geophysical Engineering (2014), Istanbul Technical University Research Highlights: His work integrates GPR with advanced computational methods to address challenges in structural integrity assessment and subsurface imaging. Recent studies include developing deep learning algorithms for object detection in GPR data and optimizing portable measurement systems for field applications. Awards: 3rd Best Presentation at the 5th Virtual Student Conference (Society of Exploration Geophysicists, 2021) Grants/Advising: No specific grants or advisee information is available in the provided texts. His current role as a Research Assistant involves academic duties within the department.

Ali Danandeh Mehrمشاهده پروفایل

استاد

• Stochastic Hydrology
• Hydroinformatics
• Extreme Hydrologic Events
• +۱ مورد دیگر

Ali Danandeh Mehr is a Professor in the Department of Civil Engineering at Antalya Bilim University, Turkey, with a focus on stochastic hydrology, hydroinformatics, and climate change impacts on water resources. He has held adjunct research positions at the University of Tabriz (Iran), Middle East University (Jordan), and the University of Oulu (Finland). PhD in Civil Engineering from Istanbul Technical University Bachelor’s degree from Islamic Azad University His research spans drought forecasting , extreme hydrologic events , and hydroclimatic modeling , leveraging advanced machine learning and hybrid algorithms. Recent work includes the S-Transformer deep learning model, MOGGP multi-objective genetic programming, and Wavelet-Entropy Clustering for drought risk mapping. He has authored over 90 peer-reviewed journal articles and six books, with recognition as a World’s Top 2% Scientist (Stanford/SCOPUS, 2019–2022) and Top 1% Highly Ranked Scholar (ScholarGPS™, 2022). Current roles include Associate Editor for Discover Water (Springer) and J. Civil. Env. Eng. (University of Tabriz).

• Thermodynamics
• Heat Transfer
• Exergy Analysis
• +۷ مورد دیگر

Prof. Kerim Mehmet Murat Tunç is a distinguished faculty member at İstanbul Bilgi University, where he has been serving as a Professor in the Industrial and Systems Engineering Department since September 2013. Previously, he held academic positions at Yeditepe University and the Technical University of Istanbul, where he advanced from Research Assistant to full Professor. His expertise lies in thermodynamics, heat transfer, exergy analysis, and energy systems, with a strong focus on industrial applications in steel production and renewable energy. His educational background includes a PhD and MS in Mechanical Engineering from the Technical University of Istanbul, and a Postdoctoral Fellowship from the University of New Brunswick, Canada. He has also been awarded prestigious research scholarships from Belgium, Canada, and Italy. His research spans energy modeling, sustainable power generation, and computational analysis of thermal systems. His recent publications reflect a deep engagement with topics such as geothermal energy, wind power optimization, solar plant investments, and climate policy impacts on energy systems in Turkey. He frequently collaborates with students and colleagues on interdisciplinary projects involving exergy efficiency, hydro scheduling, and biomedical modeling. His scientific awards include the Belgian Government Predoctoral Scholarship, Von Karman Institute Research Scholarship, and postdoctoral fellowships from the University of New Brunswick and ICTP, Italy. Belgian Government Predoctoral Research Scholarship, 1978 Von Karman Institute Research Scholarship, 1982 University of New Brunswick, Canada Postdoctoral Fellowship, 1983 International Center For Theoretical Physics (ICTP), Italy, Research Scholarship, 1986 Prof. Tunç has advised numerous graduate students, including Dr. Ünal Çamdalı and Dr. Sedat Şişbot, and has led research in computer-integrated manufacturing, energy policy, and industrial process optimization. He has also contributed to engineering education through textbooks in programming and heat transfer. He is a member of the American Society of Mechanical Engineers (ASME). His work continues to influence both academic research and industrial energy practices in Turkey and beyond.

• Robotics
• Artificial Intelligence
• Image Processing
• +۴ مورد دیگر

Arda İnceoğlu is a Lecturer in the Department of Computer Engineering at the Faculty of Computer and Information, Istanbul Technical University, where he has served since 2021. His academic career is entirely rooted at this institution, having completed all degrees there. His educational qualifications include: Ph.D. in Computer Engineering, Istanbul Technical University (2018) M.Sc. in Computer Engineering (with thesis), Istanbul Technical University (2015-2018) B.Sc. in Computer Engineering, Istanbul Technical University (2011-2015) Dr. İnceoğlu's research spans robotics, artificial intelligence, and image processing, with specialized expertise in robot manipulation failure detection, multimodal sensor fusion, 3D facial animation from audio, and generative models. His work consistently applies deep learning techniques to solve complex problems in unstructured environments. Analysis of his 11 research outputs (2015-2024) reveals a dominant focus on robotic perception and manipulation, particularly through multimodal frameworks for failure anticipation. His publications demonstrate methodological innovation in knowledge distillation for error prediction, sensor fusion architectures, and cross-domain applications of generative models in architecture and animation. No information is available regarding scientific awards, student advisement, research grants, or laboratory affiliations.

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.

• Computer Vision
• Deep Learning
• Machine Learning
• +۳ مورد دیگر

Furkan Eren Uzyıldırım is a Researcher at the Computer Engineering Department of İzmir Institute of Technology (IZTECH). He holds a BSc (2014), MSc (2016), and PhD (2022) in Computer Engineering from IZTECH. His research focuses on computer vision and deep learning, with contributions to plane estimation, object detection, and feature matching. Education: BSc in Computer Engineering, İzmir Institute of Technology (2014) MSc in Computer Engineering, İzmir Institute of Technology (2016) PhD in Computer Engineering, İzmir Institute of Technology (2022) Research Interests: Computer Vision and Deep Learning, with emphasis on applications in autonomous systems, image segmentation, and 3D scene analysis. His work includes developing unsupervised learning techniques for plane estimation and robust keypoint matching algorithms for object recognition. Grants & Projects: TÜBİTAK 1512: Safe and secure autonomous driving technologies via image segmentation and object identification TÜBİTAK 1512: Smart agricultural technologies for crop monitoring using unmanned systems Labs & Teams: Member of the Visual Intelligence Research Group (VIRG), focusing on advancing computer vision and AI applications.