جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Medical Image Computing
• Computer Vision
• +۹ مورد دیگر

Gözde Ünal is a Professor at Istanbul Technical University (ITU) in the Department of Artificial Intelligence and Data Engineering, under the School of Computer and Informatics. She has held leadership roles including Deputy Dean and former Director of the Application and Research Center. She previously served as Associate and Assistant Professor at Sabancı University and taught at Georgia Institute of Technology. Education: Ph.D., Electrical and Computer Engineering, North Carolina State University (1998–2002) M.Sc., Electrical and Electronics Engineering, Bilkent University (1996–1998) B.Sc., Electrical and Electronics Engineering, Middle East Technical University (1992–1996) Her research focuses on medical image computing, computer vision, deep learning, augmented and virtual reality, and AI for healthcare . She specializes in image segmentation, point cloud processing, and surgical scene analysis. Her work bridges computer science with biomedical applications, particularly in MRI, ultrasound, and dermoscopic imaging. She leads interdisciplinary research in both medical and cultural heritage domains. The recent publications (2021–2025) highlight a strong trend in deep learning for medical image segmentation , adversarial attacks on point clouds , AI in surgical skill assessment , and cultural heritage digitization using 3D point clouds . Her work increasingly employs transformers, self-supervised learning, and multimodal fusion, with a focus on robustness and real-world deployment. Scientific Awards: Fakülte Yılın Seçkin Eğitimcisi Ödülü, ITU, 2018 Marie Curie Alumni Association Career Award, 2017 GENÇ BİLİM KADINI, L’Oréal Turkey, 2010 GEBİP, Turkish Academy of Sciences, 2010 She has supervised numerous students and research projects, securing grants from EU and TTO (Technology Transfer Office). Her projects include AI-based optimization in banking, AI for assisted reproduction, deep learning for quality control, and normalization of multimodal brain networks. She leads a dynamic research group working on cutting-edge AI applications. She is actively involved in professional societies: President of the Marie Curie Alumni Association Turkish Chapter, member of MICCAI, IEEE, and TMRD. Her lab focuses on AI-driven solutions in medical imaging and heritage preservation, with strong international collaborations, particularly in Europe.

Kayhan Kaplanمشاهده پروفایل

مدرس

• Visual Communication Design
• 3D Animation
• Cultural Heritage Conservation
• +۳ مورد دیگر

Kayhan Kaplan is a Lecturer at the Department of Visual Communication Design, Faculty of Communication, Hasan Kalyoncu University. He holds a PhD in Landscape Architecture from Atatürk University and a 3D Animation certificate from New York Film Academy. PhD: Atatürk University, Landscape Architecture (2002) MS: New York Film Academy, 3D Animation (2012) BS: Atatürk University, Landscape Architecture (1991) His research focuses on 3D animation for historical reconstruction , cultural heritage visualization , and environmental impact analysis . Recent work includes digital modeling of ancient Antioch and conservation strategies for Turkish cultural sites. Collaborative studies span industrial visualization , forensic animation , and climate change mitigation in river basins. His publications demonstrate expertise in 3D rendering engines , animated narrative design , and ecological monitoring systems . Collaborations with environmental scientists and engineers highlight interdisciplinary applications of visual communication tools. As a full-time faculty member, he contributes to curriculum development in visual design and technology integration in communication. His work bridges digital humanities and scientific visualization through practical implementations in cultural and industrial contexts.

Hayriye Altural Özkanمشاهده پروفایل

استادیار

• Biomedical Engineering
• Microfluidics
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Hayriye Altural Özkan is an Assistant Professor at the College of Engineering and Architecture, Kastamonu University , Turkey, specializing in Biomedical Engineering and Bioelectronics. Her research spans artificial intelligence in healthcare , microfluidics , and robotic rehabilitation systems , with a focus on diagnostics and wearable technologies. PhD in Electrical and Electronics Engineering (2011), MSc in Electronics Engineering (2005), and BSc in Electronic Engineering (2002) from Erciyes University Postdoctoral research at Boston University (2013-2015) and Iowa State University (2015) Her work involves AI-driven medical diagnostics (e.g., sleep apnea, coronary artery disease), photoacoustic imaging for diabetes detection, and robotic exoskeletons for cerebral palsy rehabilitation. She has published extensively in SCI-indexed journals and conferences. Recent projects include aluminum nitride-based surface acoustic wave devices (2020-2023) and optofluidic microalgae screening systems (2013-2015). Her scientific awards include: TÜBİTAK BİDEB (2013) She has supervised master's theses on: Gait analysis visualization (Gizem Örek, 2025) AI-based sleep apnea diagnosis (Bahar Nazlı, 2021) Photoacoustic diabetes detection (Hajer Al-Jebury, 2020) As co-author of 2 books and editor of the 2023 textbook Biyomedikal Mühendisliğine Giriş , she contributes to academic pedagogy in biomedical instrumentation and microsystems.

Arif Tanju Erdemمشاهده پروفایل

استاد

• Digital Video Processing
• Computer Graphics
• Computer Vision
• +۲ مورد دیگر

Arif Tanju Erdem serves as Professor of Computer Science and Vice Rector for Academic Affairs at Ozyegin University, Istanbul. He joined the university in 2009 after 18 years at Eastman Kodak Research Laboratories and as CTO of Momentum, A.S., a digital media technologies company he co-founded. His leadership roles include Dean of the School of Engineering (2014-2018) and Head of Computer Science Department (2012-2014). His academic credentials feature: Ph.D. in Electrical Engineering, University of Rochester (1990) M.S. in Electrical Engineering, University of Rochester (1988) Dual B.S. degrees in Electrical & Electronics Engineering and Physics, Boğaziçi University (1986) Erdem's research centers on digital video processing and computer graphics with expanding applications in computer vision and machine learning. His foundational work in bispectrum analysis and video compression evolved into modern applications including face recognition systems, augmented reality tracking, and sensor fusion. Current investigations focus on overcoming data labeling challenges in biometric systems and developing robust motion tracking solutions for immersive technologies. Analysis of his recent publications (2012-2023) reveals three dominant research trajectories: (1) Advancements in face recognition using curriculum and semi-supervised learning techniques, (2) Precision sensor fusion for augmented reality through IMU-camera calibration and occlusion handling, and (3) Educational technology innovations through gamified learning systems. His work consistently bridges theoretical signal processing with practical implementations in medical monitoring, entertainment, and education. Professional service highlights include ISO-MPEG committee membership (1991-1998), IEEE Signal Processing Society leadership roles across Rochester, Turkey, and Region 8 chapters, and editorial contributions to Signal Processing: Image Communication. He has organized major conferences including the 3DTV Conference (2011) and IEEE Turkey Signal Processing Conference (2012).

KÜBRA UYARمشاهده پروفایل

مدرس

• Artificial Intelligence
• Computer Vision
• Medical Image Analysis
• +۲ مورد دیگر

KÜBRA UYAR is a Lecturer at Alanya Alaaddin Keykubat University's Rafet Kayış Faculty of Engineering, Department of Computer Engineering. She previously worked as a Research Assistant at Selçuk University's Faculty of Technology (2022-2023) and continues her academic contributions in image processing and artificial intelligence. PhD in Computer Engineering (2022), Selçuk University MSc in Computer Engineering (2017), Selçuk University BSc in Computer Engineering (2014), Melikşah University Double Major in Mathematics (2014), Melikşah University Her research focuses on Artificial Intelligence , Computer Vision , and Medical Image Analysis , with a strong emphasis on Machine Learning and Image Processing . Current work includes developing explainable AI models for retinopathy diagnosis and optimizing CNN architectures for biomedical applications. Recent publications highlight trends in Deep Learning for agriculture (chestnut classification), Medical Imaging (retinopathy, leukocyte detection), and Optimization (CNN hyperparameters, B-spline algorithms). Her work bridges Computer Science with Healthcare and Industrial Applications . Key projects include the Data-Intensive and Computer Vision Research Laboratory Infrastructure Project (2020-2021) and the Selçuk University Weather Monitoring System (2018-2020), both funded by higher education institutions.

Baran Kaynakمشاهده پروفایل

استادیار

• Cloud Manufacturing
• Blockchain Technology
• Resource Allocation
• +۵ مورد دیگر

Baran Kaynak serves as an Assistant Professor in the Department of Information Systems Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has held academic positions since 2013 (promoted from Lecturer to Assistant Professor in 2022). His institutional affiliation spans teaching, research, and project leadership within Turkey's higher education framework. His educational trajectory culminates in a Doctorate in Industrial Engineering from Sakarya University (2012-2021) with thesis work on Blockchain-Based Cloud Manufacturing Model , preceded by a Master's degree (2011-2013) focusing on wireless sensor networks in manufacturing logistics and a Bachelor's in Industrial Engineering (2007-2011) from the same institution. Dr. Kaynak's research integrates cloud computing, blockchain, and AI to solve industrial and environmental challenges. Core contributions include hybrid decision support systems for cloud manufacturing resource allocation using genetic algorithms and AHP, GPU-accelerated solar potential analysis tools, and custom web components for earth science data (e.g., Geo-WC for NOAA/USGS integration). His work bridges theoretical algorithms with practical implementations in manufacturing, renewable energy, and hydrological systems. Recent publications (2023-2025) reveal expanding applications: digital twin frameworks for urban flood analysis, IoT platforms for hydrological education (HydroSignal), and mmWave sensor-based anomaly detection in assembly lines. These works consistently demonstrate cross-disciplinary innovation, particularly in adapting blockchain for secure resource sharing and developing real-time analytics for environmental monitoring. He leads the UZEP project (2020), a Sakarya University-funded cloud-based distance education platform developed during the pandemic. While no formal student advisees are listed, his research includes student consultancy services using AI for course grade prediction and adaptive neuro-fuzzy systems for academic success modeling. Dr. Kaynak collaborates with Sakarya University's Distance Education Research and Application Center and contributes to open-source tools for earth science organizations. His current work focuses on city-scale digital twins for climate resilience and blockchain-enhanced manufacturing ecosystems, positioning him at the intersection of industrial informatics and sustainable technology development.

Kayhan AYARمشاهده پروفایل

استادیار

• Virtual Reality
• Information Security and Cryptology
• 3D Computer Graphics
• +۳ مورد دیگر

Kayhan AYAR is an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Computer Engineering. His expertise spans Virtual Reality, Information Security, Cryptology, and 3D Computer Graphics, with a focus on simulation-based educational technologies and haptic interaction systems. Doctorate: 2010–2020, Sakarya University (Thesis: 3D Image of MIG-MAG Welding Seam using Voxified Paraboloid) Master's: 2008–2010, Sakarya University (Thesis: DirectX-based 3D Game Engine Design) Bachelor's: 2000–2007, Sakarya University His research explores virtual welding simulators, voxelization techniques, and real-time haptic applications. Key publications include 15 recent articles (2010–2024) on topics like 3D modeling, neural networks in welding training, and VR-based security applications for energy infrastructure. He has contributed to international conferences and journals such as the Turkish Journal of Electrical Engineering and Computer Sciences and Journal of Materials Education . His work includes a 2014 patent for a virtual welding simulator and participation in TÜBİTAK-funded projects. Teaching responsibilities include courses in Game Programming, Data Structures, Computer Graphics, and Parallel/Distributed Systems, alongside advising graduation projects and specialization areas.

Nurdal Watsujiمشاهده پروفایل

استادیار

• Electrical-Electronics Engineering
• Image Processing
• Signal Processing
• +۱ مورد دیگر

Nurdal Watsuji serves as Assistant Professor in the Department of Electrical and Electronics Engineering at Gaziantep University's Faculty of Engineering, specializing in Electrical-Electronics Engineering with research emphases on Image Processing, Signal Processing, and Digital Design. His academic foundation includes: Doctorate in Electrical and Electronic Engineering from Imperial College London (1987-1991) Degree in Electrical-Electronic Engineering from Middle East Technical University, Gaziantep (1982-1985) Licence in Electrical Engineering from Middle East Technical University, Gaziantep (1975-1981) Watsuji's research integrates theoretical signal processing with practical engineering applications, particularly in LED/OLED lighting systems and image analysis. His work demonstrates consistent innovation in optical efficiency optimization, compressed sensing algorithms, and wavelet-based texture classification, bridging electrical engineering principles with real-world implementation challenges in energy systems and computer vision. Publication analysis from 2003-2016 reveals evolving expertise from foundational wavelet techniques to advanced optical efficiency modeling in solid-state lighting. The recurring theme involves mathematical optimization of signal/image processing methods for specific engineering constraints, with significant contributions to nonconvex compressed sensing and LED reflector design. His graduate mentoring spans eight students: PhD candidates: İpek Atık (2016) on LED reflector optimization and Taner Ince (2012) on compressed sensing Master's students: Ugur Polat (2022) on energy analyzers, Gulden Akay Ozbay (2008) on hand recognition, Taner Ince (2006) on medical image processing, Recep Oz (2004) on 3D rendering, Omer Cengiz Celebi (2003) on volume rendering, and Bayram Kara (2003) on wavelet texture analysis This diverse portfolio reflects sustained engagement with computational methods across lighting systems, biomedical imaging, and computer graphics applications.

Fabio Tosiمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +۳ مورد دیگر

Fabio Tosi is a Junior Assistant Professor (RTDA) at the Department of Computer Science and Engineering (DISI) at the University of Bologna, where he teaches the Master's course 'Accelerated Computing Systems' in the Computer Engineering program, focusing on CUDA programming. Previously, he served as an Adjunct Professor for 'Fundamentals of Computer Science' in the Mechatronics program at the Department of Electrical, Electronic, and Information Engineering. Dr. Tosi's research focuses on computer vision and machine learning, with particular emphasis on 3D reconstruction from images and deep stereo matching. His work bridges theoretical advancements with practical applications in depth estimation, neural radiance fields, and 3D scene understanding. He has made significant contributions to the field through his research on neural disparity refinement, stereo matching under challenging conditions, and the integration of NeRFs with traditional stereo techniques. His recent publications demonstrate a strong trajectory in advancing stereo matching techniques, with notable works including 'Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail' (CVPR 2025), 'Diffusion Models for Monocular Depth Estimation' (ECCV 2024), and 'Self-Evolving Depth-Supervised 3D Gaussian Splatting from Rendered Stereo Pairs' (BMVC 2024, Best Poster Award). His research shows a clear progression from foundational stereo matching techniques toward more robust, zero-shot, and multi-modal approaches that can handle challenging real-world scenarios. Dr. Tosi has received several prestigious awards including the Best PhD Thesis Award from the Italian Association for Research in Computer Vision, Pattern Recognition and Machine Learning (CVPL), the Best Poster Award at BMVC 2024, and multiple Outstanding Reviewer recognitions at major computer vision conferences including CVPR and ECCV. He serves as Associate Editor for the journal Pattern Recognition (Elsevier) and holds significant roles in major conferences as Area Chair for CVPR 2026, Associate Editor for IROS 2025, and Area Chair for ICIAP 2025. His leadership in the computer vision community extends to maintaining the 'Awesome-Deep-Stereo-Matching' repository, which has become a valuable resource for researchers in the field. Dr. Tosi completed his PhD at the University of Bologna in 2021 under Professor Stefano Mattoccia, following his Master's (2017) and Bachelor's (2014) degrees from the same institution. During his PhD, he was a visiting student at the Max Planck Institute for Intelligent Systems and the University of Tübingen in 2020, working with Professor Andreas Geiger in the Autonomous Vision Group.

• Additive Manufacturing
• CAD/CAM
• Computational Geometry
• +۳ مورد دیگر

Ulaş Yaman is an Associate Professor in the Department of Mechanical Engineering at Middle East Technical University (METU) in Ankara, Turkey. He received his B.Sc. in Mechanical Engineering (2007), M.Sc. in Mechanical Engineering (2010), and Ph.D. in Mechanical Engineering (2014) from METU, with a minor in Mechatronics. His academic career includes roles as a Visiting Assistant Professor at Purdue University (2014-2015) and research positions at METU. His research specializes in additive manufacturing, CAD/CAM systems, computational geometry, and embedded control systems. Key areas include 3D printing optimization, FDM process enhancements, CNC command generation, and hybrid manufacturing technologies. Recent work explores Industry 4.0 integration, structural optimization for 3D-printed artifacts, and novel fabrication pipelines like LIPRO. Yaman's publications demonstrate strong focus on manufacturing innovations, with recurring themes in real-time command generation, material behavior in 3D printing, geometric algorithms for production, and educational tools for control engineering. His work frequently combines hardware implementation with computational efficiency. Scientific Awards: BEST PAPER AWARD - IEEE 8th Workshop on Intelligent Solutions in Embedded Systems (2010) Research Grants: TÜBİTAK 1001: A Smart- and Hybrid Manufacturing System Utilizing Additive Manufacturing Methods and Machining (2017-2020) TÜBİTAK 3001: A Novel Design and Fabrication Pipeline for 3D Printers: LIPRO (2017-2018) ODTÜ-BAP: Improving the Dimensional Accuracy of 3D Printed Artifacts (2016) He leads the Laboratory for Intelligent Production Systems (LIPRO) with six research assistants, focusing on additive manufacturing, computational geometry, and embedded systems. Current projects include developing multi-axis hybrid manufacturing systems and novel CAD/CAM architectures.

• Animation
• 3D Modeling
• Motion Capture
• +۴ مورد دیگر

Dr. Ali Aycan Gürbüz serves as Doctor Lecturer (Assistant Professor) in the Department of Cartoon and Animation at Dumlupinar University's Faculty of Fine Arts. With continuous service since 2011, he teaches extensive undergraduate and graduate coursework while leading research in animation production technologies and arts education methodology. His educational background includes: Bachelor's in Business Administration, Anadolu University (2004-2007) Bachelor's in Painting, Dumlupinar University (2006-2007) Bachelor's in Visual Communication Design, Dumlupinar University (2007-2010) Master's in Graphics, Dumlupinar University (2011-2014) Proficiency in Arts (doctoral equivalent), Eskişehir Osmangazi University (2015-2020) Research focuses on motion capture integration, 3D printing applications for animation assets, and optimizing physical learning environments for audiovisual education. His work bridges technical innovation with pedagogical practice in cartoon and animation production. Recent publications (2022-2025) demonstrate applied research in animation technology development and arts education, with significant contributions to motion capture documentation and workshop design principles. Key themes include hybrid digital-physical production workflows and environmental factors affecting creative learning. Current research leadership includes: 'Young Entrepreneurs on the Path to Creative Cultural Industries' (2022-2024) 'Increasing psychological well-being through art practices' (2024) 'Effects of Physical Features of Workshops on Learning' (2023-2024) He advises Master's students through Thesis Management courses and supervises undergraduate animation projects within the department's studio environment.

• Information Systems
• Image Processing
• Machine Learning
• +۱ مورد دیگر

Dr. İdris Kahraman serves as a Lecturer in the Department of Computer Engineering at Karabuk University's Faculty of Engineering, where he has held academic positions since 2010. His current role as Doctor Research Assistant (2024-present) follows over a decade as a Research Assistant, during which he completed his PhD while teaching undergraduate courses including Algorithms, Introduction to Computer Engineering, and Engineering Ethics. His educational background demonstrates progressive specialization: PhD in Computer Engineering, Karabuk University (2014-2019) Master's Degree in Computer Engineering, Karabuk University (2010-2014) Bachelor's Degree, Turkish Military Academy Command (2003-2007) Dr. Kahraman's research bridges theoretical computer science and practical geospatial applications, with four core pillars: Information Systems development, Image Processing techniques, Machine Learning implementations, and Artificial Intelligence solutions. His work consistently applies these to satellite imagery analysis, 3D modeling, and real-time detection systems, creating tangible outputs like AR tourism applications and automated protozoa identification tools. Publication trends reveal evolving expertise from foundational 3D campus modeling (2011-2013) through satellite road detection systems (2015-2017) to current biomedical and urban analytics applications. The 2024 Applied Sciences paper on real-time protozoa detection represents his most sophisticated integration of deep learning with practical instrumentation. Research funding shows sustained activity through university-supported projects since 2011: Current: Principal researcher on 3D building modeling project (2024-2026) Recent: Principal investigator for neural network road detection project (2017-2018) Historic: Multiple roles in satellite imagery and 3D campus system projects (2011-2024) Though no formal laboratory is documented, Dr. Kahraman operates within Karabuk University's collaborative research ecosystem, maintaining a decade-long productive partnership with Prof. İsmail Rakıp Karaş and contributing to the institution's geographic information systems research cluster through both technical projects and curriculum development.