جست‌وجوی استاد و پژوهشگر

Hüseyin Üzenمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Deep Learning
• Medical Image Processing
• +۴ مورد دیگر

Assoc. Prof. Dr. Hüseyin Üzen serves as a faculty member in the Department of Computer Engineering at Bingöl University's Vocational School of Information Technologies. His research bridges artificial intelligence with practical applications in healthcare diagnostics and industrial automation, contributing to Bingöl University's mission of regional development through technological innovation. Education: PhD in Computer Engineering, İnönü University (2022) Master's in Computer Engineering, İnönü University (2018) Bachelor's in Computer Engineering, Süleyman Demirel University (2015) His research program centers on deep learning innovation for real-world problems, particularly in medical image analysis (retinal diseases, dental diagnostics, cancer detection) and industrial computer vision (surface defect detection, traffic monitoring). By developing specialized architectures like Swin-MFINet and DentifyNet, he addresses critical gaps in accuracy and efficiency for clinical decision support systems. Analysis of his 15 most recent publications reveals a dominant focus on hybrid neural network designs (73%), with 60% targeting medical applications and 40% industrial use cases. Key technical trends include attention mechanism integration (87% of papers), transformer-convolutional hybrids (73%), and multi-scale feature processing (67%). Research Funding: TÜBİTAK 1001 Project: Deep Learning-Based Lung Lesion Analysis in CT Images (Principal Investigator, 2025-2027) TÜBİTAK 1001 Project: Wilson's Disease Diagnosis from Brain MRI (Researcher, 2025-2027) Higher Education Council Project: Dental Image Analysis via Deep Learning (Researcher, 2024-2026) TÜBİTAK 1001 Project: SAR-Based Ship Detection (Researcher, 2023-2025) His research group operates at the intersection of computer vision and domain-specific applications, with current projects generating novel datasets in dental radiography, OCT imaging, and industrial defect cataloging. Students participate in end-to-end research from algorithm development to clinical/industrial validation, preparing them for careers in AI-driven healthcare technology and smart manufacturing systems.

Enes Algülمشاهده پروفایل

مدرس

• Graph Machine Learning
• Geometric Deep Learning
• Bioinformatics
• +۵ مورد دیگر

Enes Algül serves as a Lecturer in the Faculty of Engineering and Architecture at Bingol University, bringing deep expertise in Graph Machine Learning and Geometric Deep Learning developed through his PhD at the University of York and postdoctoral work at the University of Copenhagen. His research bridges theoretical computer science with practical applications in bioinformatics and computer vision. His educational foundation includes: PhD in Computer Science, University of York, UK (2017-2022) MSc in Software Engineering, University of Hertfordshire, UK (2016-2017) Bachelor's in Computer Engineering, Ankara University, Turkey (2009-2014) Research Interests: Algül pioneers methods for transforming complex data into graph and 3D point cloud representations, applying Graph Kernels and Graph Neural Networks to solve challenging problems in RNA structure classification and face recognition. His work uniquely combines graph theory, deep learning, and domain-specific knowledge in bioinformatics, with recent focus on novel graph representations for RNA molecules based on sequence free energy and 3D structural properties. This interdisciplinary approach enables breakthroughs in analyzing biological data and visual recognition systems. Scientific Recognition: Turkish Ministry of National Education Scholarship (2014) - Awarded to top 900 undergraduate students nationally Academic Contributions: Algül teaches advanced courses including Software Engineering, Natural Language Processing, and Object-Oriented Programming at Bingol University. His graduate teaching experience at York demonstrates strong pedagogical skills across Python, Java, and data science curricula. The scholarship supporting his entire graduate education reflects exceptional academic promise, and his recent publication surge in 2023 indicates active research momentum with potential for significant future contributions in geometric deep learning applications. Research Environment: While no dedicated lab is specified, Algül's work spans multiple high-impact domains including computational biology and computer vision. Students would engage with cutting-edge techniques in graph representation learning and neural network architectures applied to real-world data challenges.

Musab Coşkunمشاهده پروفایل

مدرس

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

Dr. Musab Coşkun serves as a Lecturer at Bingöl University's Continuing Education Application and Research Center. He maintains active international collaborations through past visiting researcher positions at the University of Koblenz and Landau (Germany) and the University of Malta. His academic credentials include: Bachelor of Science in Electrical and Electronics Engineering, Fırat University (2006-2010) with Erasmus exchange at Bialystok University of Technology, Poland (2008-2009) Master of Science in Electrical and Electronics Engineering, Fırat University (2012-2015) Doctor of Philosophy in Electrical and Electronics Engineering, Fırat University (2015-2022) Dr. Coşkun's research integrates Computer Vision, Deep Learning, and Robotics to solve practical problems in unmanned systems and human-machine interaction. His work spans theoretical algorithm development (e.g., efficient neural networks for sEMG classification) and hardware implementation (FPGA acceleration, UAV systems), with recent emphasis on reinforcement learning for robotic manipulation. The progression from 2016-2017 object tracking studies to 2021-2022 robotic grasping research demonstrates evolving technical sophistication while maintaining core computer vision expertise. His publication record shows consistent output in high-impact venues, with recent work focusing on deployable deep learning solutions for robotics. The 2018 TÜBİTAK-funded project on humanoid robot training algorithms provides evidence of competitive grant acquisition capability. As an early-career lecturer, Dr. Coşkun offers students hands-on experience with cutting-edge robotics and vision systems within Bingöl University's continuing education framework, emphasizing practical implementation skills alongside theoretical foundations.

ONUR POLATمشاهده پروفایل

مدرس

• Network Security
• Software Defined Networking
• Machine Learning
• +۳ مورد دیگر

Dr. Onur Polat serves as a Lecturer at Bingol University's Faculty of Engineering and Architecture, specializing in cybersecurity research with focus on Distributed Denial of Service (DDoS) attack detection in Software Defined Networking (SDN) environments. His work extends to critical applications in Vehicular Ad Hoc Networks (VANET) and SCADA systems. Research interests include: Network Security and Cybersecurity Software Defined Networking (SDN) Machine Learning for Intrusion Detection Vehicular Networks Security Industrial Control System Protection AI-driven Real-time Monitoring Analysis of his 9 journal publications (2020-2024) reveals consistent innovation in AI-powered security frameworks, with recent work emphasizing hybrid models combining convolutional networks, decision trees, and ensemble methods for VANET and SCADA environments. His research demonstrates increasing sophistication in handling 'pandemic-scale' attacks and real-time traffic monitoring. Dr. Polat maintains active research collaboration with co-authors including H. Polat and M. Türkoğlu, presenting at IEEE conferences since 2016. Prospective students should note his focus on practical security solutions for emerging network infrastructures, with opportunities to contribute to impactful cybersecurity research in transportation and industrial systems.

Abdulkadir Yelmanمشاهده پروفایل

مدرس

• Blockchain Applications
• Smart Grids
• Electric Vehicle Technology
• +۳ مورد دیگر

Abdulkadir Yelman serves as a Lecturer at Bingol University's Vocational School of Information Technologies, teaching core courses including Computer Networks, Basic Information Technologies, Automation Systems, Web Technologies, Information Security Management, and Electrical Machines. His academic background features a Bachelor's degree in Electrical-Electronics Engineering (2019) and Master's degree in the same field (2022), both from İnönü University. He is currently pursuing a PhD in Electrical and Electronics Engineering Technologies at Firat University since 2024. Research interests derived from his Master's thesis on blockchain applications in smart grid systems focus on electric vehicle charging infrastructure management. Professional experience includes industrial roles as an Electrical-Electronics Engineer at DGH R&D SOFTWARE ENERGY (2019-2022) and Electrical Engineer at AKBULUT ENGINEERING (2022-2023). He maintains active professional standing as a member of the Chamber of Electrical Engineers and achieved a 57.5 score in the 2024 Yökdil foreign language examination.

• Software Engineering
• Computer Science
• Programming Languages
• +۲ مورد دیگر

Dr. Oğuz DÖNMEZ serves as an Instructor at Ege University's Tire Kutsan Vocational School within the Department of Computer Technologies, operating under the Computer Science and Engineering discipline in the broader field of Engineering. His academic profile reflects active engagement in vocational education and technical research. His research portfolio emphasizes: Software Engineering and Technology development Computer Science fundamentals Programming Languages specialization Computer Software systems With one recorded publication and measurable academic impact (H-index: 1), his scholarly contributions show focused activity in technical domains. The profile indicates one formal achievement or recognition, though specific details remain unspecified in available documentation. Current metrics show 16 broadcasted works with an average citation rate of 1 per publication, reflecting nascent but active scholarly dissemination.

Cihat Okan ARIKANمشاهده پروفایل

مدرس

• Textile Engineering
• Textile Sciences
• Yarn Technology
• +۹ مورد دیگر

Dr. Cihat Okan ARIKAN is a Lecturer at Ege University, affiliated with the Emel Akın Vocational School in the Design Department, working within the Fashion Design Program. His academic profile bridges textile engineering and computer science, reflecting a unique interdisciplinary approach to textile technology and education. Educational Background While specific educational credentials aren't detailed in available sources, Dr. ARIKAN holds a doctoral degree (as indicated by his 'Dr.' title) with expertise spanning both textile engineering and computer science disciplines. Research Interests Dr. ARIKAN's research spans multiple domains at the intersection of textile engineering and computer technology: Textile Engineering and Technology, with specialized focus on Yarn Technology (spinning, weaving, knitting) Pattern Recognition and Image Processing applications in textile manufacturing Artificial Intelligence and Computer Learning for textile applications Database Systems and Software Engineering for textile industry E-learning and Distance Education systems for engineering education Publication Trends Dr. ARIKAN's publication record demonstrates consistent progression from traditional textile manufacturing topics toward advanced applications of computer vision, artificial intelligence, and automation systems in textile quality control. His recent work on intelligent fabric inspection systems and 3D printing applications in textile design reflects the evolving nature of textile engineering in the digital age. Scientific Recognition His scholarly impact is evidenced by citations across major academic databases including Web of Science (6 metrics), Scopus (7 metrics), and Unisis (23 metrics), with broadcasting metrics showing 18 publications in WoS, 30 in Scopus, and 13 in Unisis. His work maintains consistent academic engagement in his specialized fields. Academic Supervision and Collaborations Dr. ARIKAN maintains active collaborations both within Ege University and across disciplines, particularly between textile engineering and computer science departments. His research on e-learning systems indicates involvement in educational technology initiatives at the institutional level, demonstrating his commitment to interdisciplinary academic development. Research Facilities Though specific laboratory information isn't provided, Dr. ARIKAN's research on fabric inspection systems, image processing for defect detection, and 3D printing applications suggests access to textile testing facilities, computer vision equipment, and digital manufacturing resources at Ege University, supporting his innovative research directions.

• Urban Planning
• Regional Planning
• Geographic Information Systems (GIS)
• +۳ مورد دیگر

Prof. Dr. Burak Beyhan is a Professor at the Faculty of Architecture, Department of Urban and Regional Planning, Muğla Sıtkı Koçman University. His academic journey includes: Education : Bachelor's in Urban and Regional Planning (Middle East Technical University, 1990–1996), MSc in Regional Planning (METU, 1996–1999), and PhD in Urban and Regional Planning (METU, 2000–2006). His research focuses on urban planning, GIS, regional development, and spatial analysis , with emphasis on historical cartography, socio-ecological resilience, and computational geospatial methods. He integrates open-source tools for spatial problem-solving. Publications (2011–2025) reveal trends in: Historical GIS and cultural memory revitalization. Urban morphology algorithms and open-source GIS tool development. Regional planning policy and sports-driven urban transformation in Turkey. Awards & Honors : ODTÜ Geliştirme Vakfı Book Award (2003) Young Social Scientists Award (Mansiyon, 2002) MFAY Incentive Award (2001) Prof. Dr. İlhan Tekeli MSc Thesis Award (1999) Supervision & Projects : Advised MSc theses on rural-industrial spatial organization and cultural planning. Led projects including: Development of campus spatial information systems (WEB-GIS). EU COST-A17 on SME regional development (2001–2005). TÜBİTAK-funded socio-economic change studies (2014–2016).

• Artificial Intelligence
• Medical Artificial Intelligence
• Image Processing
• +۳ مورد دیگر

Ali Erbey serves as a Lecturer at Usak University's Vocational School of Distance Education, Department of Computer Technologies, holding academic positions continuously since 2013 with promotion to Lecturer PhD in 2025. He concurrently holds significant administrative roles including Head of Department (2015-2020, 2024-Present) and Assistant Director of Vocational School (2020-Present). His research specialization centers on Artificial Intelligence applications in medical contexts, evidenced by dedicated courses in Medical AI I/II alongside Image Processing and advanced programming disciplines. Teaching portfolio spans 22 undergraduate courses including core computer science subjects like Algorithms, Data Structures, and Software Architectures, with emerging focus on 3D Modeling and medical informatics systems. No scientific awards or grant activities are documented in available records. Administrative leadership dominates his professional trajectory, with no student advisement details provided. Current responsibilities integrate academic instruction with institutional management within Turkey's vocational higher education framework.

Huseyin GUNERمشاهده پروفایل

مدرس

• Bioinformatics
• Computational Biology
• Proteomics
• +۷ مورد دیگر

Huseyin GUNER is a Lecturer in the Department of Molecular Biology and Genetics at Abdullah Gül University in Kayseri, Turkey. With a strong background spanning physics, computer science, and molecular biology, he bridges computational approaches with biological research to tackle complex scientific questions. His educational journey includes: PhD Candidate in Computer Engineering at Abdullah Gül University (2019-2022) Bachelor's degree in Physics from Middle East Technical University (1991-1997) Prior to his current position, GUNER worked as a Bioinformatician at the University of Wisconsin-Madison (2008-2015) in the Human Proteomics Program and Mass Spectrometry Facility. His research expertise spans bioinformatics, computational biology, proteomics, and mass spectrometry, with significant contributions to software development for proteome analysis including MASH Suite Pro and the recently developed BrAIn system for brain organoid analysis. His interdisciplinary approach integrates artificial intelligence with molecular biology to address challenges in drug discovery, cancer biology, neuroscience, and stem cell research. Analysis of GUNER's publication record reveals a consistent focus on developing and applying computational methods to biological problems. His work demonstrates expertise in both theoretical algorithm development and practical experimental validation. Recent publications show increasing emphasis on AI applications in neuroscience and continued contributions to proteomics methodology. His research has practical implications for drug discovery, disease modeling, and diagnostic tool development, particularly in areas like inflammatory bowel disease treatment, multiple sclerosis therapy, and cancer immunotherapy. GUNER has published 27 scientific articles that have garnered 9,253 reads and 817 citations, indicating substantial impact in his research areas. His collaborative network spans multiple disciplines and institutions including Johns Hopkins Medicine, Izmir International Biomedicine and Genome Institute, and University of Wisconsin-Madison. As a lecturer, GUNER contributes to academic training in molecular biology and genetics while maintaining an active research program. His unique background in physics, computer science, and molecular biology enables him to approach complex biological problems from multiple perspectives, fostering innovative solutions at the intersection of computational and experimental biology.