جست‌وجوی استاد و پژوهشگر

• Natural Language Processing
• Generative AI
• Social Computing
• +۵ مورد دیگر

Cagri Toraman is an Assistant Professor at Middle East Technical University's Computer Engineering Department, leading the Applied NLP Group. He holds a PhD in Computer Science from Bilkent University (2017) and has industry experience as Software Engineer (Havelsan 2017-2018), Postdoctoral Research Scientist (University of Central Florida 2018-2019), and NLP Team Lead (Aselsan 2020-2023). PhD in Computer Science (Bilkent University, 2017) Postdoctoral Research Scientist (University of Central Florida, 2018-2019) NLP Team Lead (Aselsan, 2020-2023) His research focuses on Natural Language Processing , Generative AI , and Social Computing , with particular emphasis on low-resource language adaptation, hate speech detection, multimodal analysis, and misinformation identification. Recent work examines dataset quality evaluation, transformer optimization with tweet-specific elements, and pejorative language disambiguation for misogyny detection. Notable achievements include receiving the Google Gemma Academic Research Award 2024 . He teaches core courses in Data Structures and Applied Natural Language Processing , emphasizing both theoretical foundations and practical implementation. Research trends show expertise across: Multilingual dataset creation (MiDe22, JL-Hate) Transformer-based hate speech detection Generative AI adaptation for Turkish Ensemble learning in socio-political event extraction Contextual word embeddings analysis Conversational system robustness

Omer Kasimمشاهده پروفایل

دانشیار

• Machine Learning
• Software Engineering
• Data Science

Dr. Ömer Kasim is an associate professor at the Faculty of Technology, Dumlupınar University. His research interests include machine learning, software engineering, and data science. He has published extensively in these areas, contributing significantly to the advancement of knowledge in these fields.

• Machine Learning
• Data Mining
• Educational Technologies
• +۷ مورد دیگر

Mustafa Yağcı is a Professor in the Department of Computer Engineering at Kırşehir Ahi Evran University's Faculty of Engineering and Architecture. He holds a PhD in Electronics and Computer Education from Sakarya University and has dedicated his career to educational technology, machine learning, and data mining. Education : PhD (2012), MSc (2005), BSc (1996) in Electronics/Computer Education Current Role : Professor (2024-), Department Chair, Academic Council Member Research Interests : His work bridges machine learning and educational technologies , focusing on computational thinking and adaptive learning systems . Notable projects include: Brain-Computer Interface for Stroke Patients Deep Learning for Tumor Detection Real-Time Face Mask Detection Scientific Impact : With over 1600 citations (h-index:16), he has published 72 articles and led 33 research projects. Awards include TÜBİTAK's Publication Incentive and Research World's Excellent Paper Award. Advising : Supervised 10 Master's theses on topics like CNN-based facial recognition and smart home security systems . Collaborated with researchers across Turkey, Egypt, and Iraq.

• Information Security and Cryptology
• Artificial Intelligence
• Computer Software
• +۳ مورد دیگر

Mehmet Ali YALÇINKAYA is a full-time Lecturer in the Department of Computer Engineering at Ahi Evran University's Faculty of Engineering and Architecture. His academic journey includes a PhD (2020) and MSc (2015) in Computer Engineering from Süleyman Demirel University, and a BSc in Electronics and Computer Education (2012). PhD: Computer Engineering, Süleyman Demirel University (2020) MSc: Computer Engineering, Süleyman Demirel University (2015) BSc: Electronics and Computer Education, Süleyman Demirel University (2012) His research focuses on Information Security and Cryptology , Artificial Intelligence , Computer Software , and Cybersecurity . Recent work includes phishing detection systems, deep learning applications for security, and AI-driven educational tools. Key article trends: 2025: NLP for violence detection in healthcare 2024: Multilayer security frameworks, AI in education, and biometric authentication 2023: Phishing defense mechanisms and agricultural pest detection He has supervised four Master's theses and collaborated with 48 researchers. Notable projects include a BCI-supported deep learning model for motor/facial analysis (2025-2027) and AI-powered educational systems for primary schools.

• Biomechanics
• Biomedical Sciences and Technologies
• Signal Processing

Serkan ÇİZMECİOĞULLARI is a Lecturer at Kırşehir Ahi Evran Üniversitesi's Vocational School of Technical Sciences, specializing in Electronics and Automation. His academic journey includes a PhD in Biomedical Engineering (2012-2023) from Istanbul University-Cerrahpaşa, a second PhD from Istanbul University (2012-2018), an MSc from Istanbul Technical University (2009-2011), and a second MSc from Boğaziçi University (2008-2009). He holds a BSc in Electrical and Electronics Engineering from Sakarya University (2001-2007). Current affiliation: Kırşehir Ahi Evran Üniversitesi (2023-present, full-time) Past affiliations: Biruni Üniversitesi (2021-2023, part-time), Istanbul Aydın Üniversitesi (2021-2022, part-time), Istanbul Medipol Üniversitesi (2018-2019, part-time), Nişantaşı Üniversitesi (2018-2019, part-time) His research focuses on Biomechanics , Biomedical Sciences and Technologies , and Signal Processing . Key themes include: Wearable motion capture systems for biomechanical modeling Electrophysiological effects of magnetic fields Neurorehabilitation robotics and clinical applications Signal processing for biomedical data filtering The 14 listed publications (2018-2024) demonstrate expertise in biomedical engineering, signal processing, and rehabilitation technology. Collaborations span institutions like İzmir Ekonomi Üniversitesi, Bezm-İ Âlem Vakıf Üniversitesi, and Girne Üniversitesi with researchers such as Aydın Akan and Yaşar Keskin. Projects include: TÜBA/TÜBİTAK-supported AC Motor Driver research (2018-2019) Modular Industry 4.0 compliant motor systems (2017-2020) Myoaction Trainer exercise technology (2024) With 28 citations and an h-index of 2, his work bridges biomedical signal processing and industrial automation applications.

• Data Structures and Algorithms
• Robotics
• Artificial Intelligence
• +۴ مورد دیگر

Mustafa AKSU is a Lecturer at Ahi Evran University, Faculty of Engineering and Architecture, Department of Computer Engineering. He holds a Doctorate (2016) from İnönü University in Computer Hardware, a Master's (2004) in Electrical and Electronics Engineering from Kahramanmaraş Sütçü İmam University, and a BSc (1998) in Computer Science Engineering from Kocaeli University. Current Position: Doctor Öğretim Üyesi (Lecturer) since 2022 Previous Role: Full-time Teaching Staff at Kahramanmaraş Sütçü İmam University (2001-2022) His research focuses on Data Structures and Algorithms , with significant contributions to skip ring/skip list innovations and their applications in robotics, artificial intelligence, and image processing. Key interests include: Algorithm optimization Machine learning applications Image segmentation techniques Mobile system development Renewable energy simulations Publications showcase expertise in data structures, robotics, and energy systems, with a recent 2024 paper on COVID-19 prediction algorithms and a 2023 book chapter on robotic simulation importance . Collaborations span institutions including İnönü University, University of Turku, and Gaziantep University. As a thesis advisor, he has guided three Master's students in 2024. Professional experience includes department chairmanship (2011-2014) and extensive teaching roles since 2001.

• Computer Software
• Programming Languages
• Green Computing
• +۳ مورد دیگر

Dr. Lecturer İbrahim ŞANLIALP is a faculty member at the Faculty of Engineering and Architecture, Ahi Evran University, specializing in Computer Hardware and Software Engineering. He holds a Ph.D. (2022) and M.Sc. (2015) in Computer Engineering from Süleyman Demirel University, alongside a B.Sc. in Electronics and Computer Education (2010). Education: Ph.D. in Computer Engineering (Süleyman Demirel University, 2015-2022) M.Sc. in Computer Engineering (Süleyman Demirel University, 2012-2015) B.Sc. in Computer Engineering (Süleyman Demirel University, 2005-2010) Diploma in Electronics and Computer Education (Süleyman Demirel University, 2005-2010) His research focuses on Computer Software and Programming Languages , with recent studies analyzing energy efficiency in code refactoring, landslide prediction using statistical methods, and machine learning applications in public health. His work spans green computing , geospatial analysis , and AI-driven classification systems. Dr. Şanlıalp has contributed to 9 publications, including 2 journal articles (SCI-Exp, TR Dizin) and 7 conference papers. His projects include "3D Environment Path-Finding Algorithms for UAVs" (2025-2026) and "Grid-Based Path Planning Simulation" (2024-2025) as principal investigator. Metrics highlight 26 total citations (Google Scholar), h-index of 1, and active collaborations with researchers from Süleyman Demirel University, Ankara Yıldırım Beyazıt University, and Niğde Ömer Halisdemir University. His teaching portfolio includes courses like "Game Programming", "Computer Concepts", and "Cybercrime" since 2022.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Assistant Professor Ayla Kayabaş is affiliated with the Faculty of Engineering and Architecture at Ahi Evran University , where she focuses on the Computer Engineering department. Her academic journey includes a PhD in Computer Engineering from Ankara Yıldırım Beyazıt University (2013-2020), a Master's Degree (2003-2011), and a Bachelor's Degree (2003-2011) from Universitaet Stuttgart. Research Interests: Her work centers on Artificial Intelligence , particularly in Natural Language Processing and Deep Learning . She has developed innovative algorithms for Turkish morphological analysis, combining finite-state automata and neural networks. Recent publications explore AI-generated text classification, reflecting her broader interest in machine learning applications. Academic Contributions: Her three key publications (2022, 2025) span neural network architectures for language processing, error correction in OCR systems, and hybrid morphological analysis frameworks. These works align with her expertise in Deep Learning , Neural Networks , and Language Modeling . Teaching and Supervision: She has supervised two Master's theses: Automatic detection of intrusion attacks in IoT networks (2023) and Student performance prediction using educational data mining (2022). Additionally, she has taught courses in Natural Language Processing, Formal Languages, Applied Machine Learning, and Software Engineering. Collaborative Impact: Collaborating with researchers from Ankara Medipol University, Ankara Yildirim Beyazit University, and Ludwig-Maximilians-Universität München, she contributes to interdisciplinary advancements in computational linguistics and AI.

Mustafa ULAŞمشاهده پروفایل

استادیار

• Data Mining
• Big Data
• Machine Learning
• +۷ مورد دیگر

Mustafa ULAŞ is an Assistant Professor in the Software Engineering Department at Fırat University, Turkey. He also serves as a University Advisor and Coordinator of the Digital Transformation and Software Office at Fırat University since October 2020. With academic roots entirely at Fırat University, he has established himself as a prominent researcher in data science and software engineering. Born in November 1981 in Elazığ, Turkey PhD in Electrical-Electronics Engineering (2011) Master's in Computer Engineering (2006) Bachelor's in Electrical-Electronics Engineering (2003) Dr. ULAŞ's research spans multiple domains of computer science and engineering with particular emphasis on practical applications. His work bridges theoretical computer science with real-world problems in healthcare, finance, and industrial systems. Recent publications reveal a strong focus on machine learning applications, especially in medical diagnostics and explainable AI, while maintaining his longstanding interest in VLF signal analysis for earthquake prediction. His publication record shows a clear evolution from foundational work in database systems and medical imaging to cutting-edge research in deep learning and explainable AI. The most recent articles (2024-2025) predominantly focus on healthcare applications of machine learning, particularly diabetes and cancer diagnosis, while maintaining parallel research streams in industrial applications, financial analytics, and drone network optimization. This multidisciplinary approach demonstrates his ability to adapt core computational techniques to diverse problem domains. Dr. ULAŞ has been actively involved in numerous research projects, including TÜBİTAK-funded initiatives such as the 'Enriched Virtual Laboratory' and 'A New Approach in Teacher Education: Effective Blended Learning.' His project portfolio spans infrastructure development, educational technology, and advanced research applications. As an educator, he teaches courses including C Programming and Algorithms, Internet-Based Programming, Server Operating Systems, and Web Project Management. His administrative roles include serving as University Advisor and Coordinator of the Digital Transformation and Software Office at Fırat University since 2020.

GÖKÇE YILDIRIMمشاهده پروفایل

مدرس

• Machine Learning
• Optimization
• Random Number Generation
• +۴ مورد دیگر

Dr. Gökçe Yildirim serves as a Doctor Lecturer at Bingöl University's Vocational School of Technical Sciences within the Department of Machine and Metal Technologies since 2019, advancing from Lecturer (2019-2025) to her current position. Her academic foundation was built at Fırat University through sequential engineering degrees culminating in a 2024 PhD in Software Engineering. Educational background: Mechatronics Engineering BSc, Fırat University (2010-2014) Mechatronics Engineering MSc, Fırat University (2014-2017) Software Engineering PhD, Fırat University (2018-2024) Her research program centers on machine learning and optimization with distinctive expertise in chaotic-system-based random number generation . This computational focus drives interdisciplinary applications across medical diagnostics, agricultural forecasting, and gaming analytics. Recent work demonstrates sophisticated integration of nonlinear dynamics with security-critical applications, reflecting both theoretical depth and practical implementation skills. Publication analysis reveals consistent output since 2018 with accelerating international engagement. The 2023 works mark significant maturation of her research identity, particularly the Chaos, Solitons & Fractals paper establishing her innovative optimization approach for chaotic random number generators. Her portfolio shows remarkable versatility across domains while maintaining core computational methodology. Scientific recognition: No major awards documented in current records Dr. Yildirim maintains active teaching responsibilities across foundational engineering disciplines while pursuing research. Her vocational school context emphasizes practical skill development, with research directly informing curriculum design. Current publications indicate ongoing projects in secure random number generation and agricultural data mining, though specific grant details remain undisclosed. No dedicated research laboratory is documented, suggesting computational work leverages shared university resources within the vocational school's applied engineering framework.

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.