Find Academic Supervisors

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +3 more

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.

• Biomedical Engineering
• Biomechatronics
• Robotics
• +2 more

Mücahit Ege serves as Assistant Professor in the Software Engineering Department at the Faculty of Engineering, Istanbul Gedik University since 2024. Previously, he held Lecturer positions in the Electronics and Automation Department at Gedik Vocational School from 2012 to 2024 across multiple academic appointments. His educational qualifications include: Doctorate in Biomedical Engineering from Kocaeli University Institute of Science (2013-2023) Master of Science in Mechatronics (with thesis) from Marmara University Institute of Science (2010-2013) Bachelor's degree in Electronics and Communications Teaching (English) from Marmara University Faculty of Technical Education (2004-2010) Dr. Ege's research integrates software engineering with biomedical applications and robotic systems. His expertise spans Biomedical Engineering, Biomechatronics, and Robotics, focusing on developing computational solutions for healthcare technologies and automated systems through interdisciplinary approaches combining software development with biomedical instrumentation.

• Computer Science
• Software Engineering
• Artificial Intelligence
• +3 more

Turgut Pura serves as an Assistant Professor in the Software Engineering Department within the Faculty of Engineering at Istanbul Gedik University. He concurrently holds appointments at Gedik Vocational School's Department of Computer Technologies, demonstrating dual institutional engagement across undergraduate and vocational academic units. His educational foundation includes a Doctorate in Computer Engineering from Istanbul Aydın University (2018-2023), Master's degree in Computer Engineering (2011-2016), Bachelor's in Computer Engineering from Istanbul Cultural University (2005-2009), and Associate Degree in Computer Programming from Beykent University (2003-2005). Doctorate: Computer Engineering, Istanbul Aydın University (2018-2023) Master's: Computer Engineering (Thesis), Istanbul Aydın University (2011-2016) Bachelor's: Computer Engineering (English), Istanbul Cultural University (2005-2009) Associate Degree: Computer Programming, Beykent University (2003-2005) Professor Pura's research spans core computer science disciplines with emphasis on Database Systems, Artificial Intelligence applications, and Algorithmic theory. His work integrates theoretical computational frameworks with practical software engineering implementations, particularly relevant to modern data-intensive systems and intelligent computing solutions. No scientific awards or fellowships were documented in available institutional records. Academic service includes progressive appointments since 2019: initial Lecturer role at Gedik Vocational School, advancement to Doctor Lecturer in 2023 across both Engineering Faculty and Vocational School units, culminating in Assistant Professor position within Software Engineering Department in 2024. Contact details indicate primary campus assignment at Eagle Campus (Internal 2136).

• Data Mining
• Cyber Security
• Big Data
• +6 more

Abdullah Orman serves as Assistant Professor in the Computer Technologies Department at Ankara Yildirim Beyazit University's Technical Sciences Vocational School since 2018, following his research assistant position at Gazi University Institute of Science starting in 2003. His academic qualifications include: Computer Systems Teaching (2001) Computer Engineering Bachelor's Degree (2022) Electronic Computer Education Master's Degree (2005) Electronic Computer Education PhD (2012) His research integrates computer science with transportation systems, specializing in data mining for cyber security applications, big data analytics in network optimization, and AI-driven pattern recognition. This work spans software engineering, database systems, and transportation technology innovation with practical implementations in secure network infrastructure. Dr. Orman has managed 25 national/international projects and supervised 4 theses, with research output comprising 48 Web of Science publications and 5 Scopus-indexed works reflecting significant scholarly impact.

Mehmet Saadeddin ÖztürkView profile

Assistant Professor

• Biomedical Optics
• Computational Imaging
• Biomedical Instrumentation
• +3 more

Mehmet Saadeddin Öztürk is a part-time Assistant Professor at Bogazici University, specializing in biomedical optics, computational imaging, and diagnostic technology development. His research integrates optical imaging, microfluidics, and AI for label-free cancer diagnostics and veterinary applications. He teaches graduate courses in biomedical optics and medical imaging with a translational engineering focus. Education Ph.D. in Biomedical Engineering, Rensselaer Polytechnic Institute (2013-2016) M.Sc. in Manufacturing Engineering, Boston University (2008-2010) B.Sc. in Electronics Engineering, Kadir Has University (2002-2006) Research Focus Dr. Öztürk's work spans four key areas: Biomedical Optics : Development of imaging/diagnostic devices Computational Imaging : Light modeling for scattering environments Biomedical Instrumentation : Hardware/software integration Preclinical/Veterinary Imaging : Small animal studies and gait analysis Publications Overview His 15 most recent publications demonstrate consistent focus on optical tomography innovations, with evolving applications in cancer diagnostics (breast cancer, glioblastoma), veterinary science (feline neuroanatomy), and thermogenetic control systems. Recent works show increased integration of AI and multimodal platforms. Awards and Honors Marie Curie Co-Fund Post-Doctoral Fellowship (EMBL, 2017-2020) Best Doctoral Thesis Award (RPI, 2016) Multiple international travel grants (ESOF 2024, WMIC 2016) Full scholarships for B.Sc. and M.Sc. degrees Professional Activities He serves as project referee for TÜBİTAK and TUSEB funding panels, reviews for leading journals including Science Advances and Nature Communications Biology , and participates in TEKNOFEST technology competitions. Current research includes developing a preclinical multimodal imaging platform for drug monitoring.

Mustafa ULAŞView profile

Assistant Professor

• Data Mining
• Big Data
• Machine Learning
• +7 more

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 YILDIRIMView profile

Lecturer

• Machine Learning
• Optimization
• Random Number Generation
• +4 more

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 ÜzenView profile

Associate Professor

• Artificial Intelligence
• Deep Learning
• Medical Image Processing
• +4 more

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 AlgülView profile

Lecturer

• Graph Machine Learning
• Geometric Deep Learning
• Bioinformatics
• +5 more

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 CoşkunView profile

Lecturer

• Computer Vision
• Deep Learning
• Robotics
• +3 more

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 POLATView profile

Lecturer

• Network Security
• Software Defined Networking
• Machine Learning
• +3 more

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.

SADIK VAROLGÜNEŞView profile

Lecturer

• Earthquake Engineering
• Structural Engineering
• Geotechnical Engineering
• +5 more

Dr. Sadik Varolguneş serves as a Dr. Lecturer in the Faculty of Engineering and Architecture at Bingol University since 2024, following 14 years as a Research Assistant at the same institution. His academic foundation includes a Civil Engineering PhD from Dicle University (2023), Master's degree (2013), and Bachelor's degree from Erciyes University (2001), with professional experience spanning construction management and municipal engineering prior to academia. His educational journey features: Bachelor's Degree in Civil Engineering, Erciyes University (2001) Master's Degree in Civil Engineering, Dicle University (2013) PhD in Civil Engineering, Dicle University (2023) Varolguneş's research bridges earthquake engineering and sustainable construction, with dual focus on seismic resilience and eco-friendly materials. He conducts field investigations of earthquake-damaged structures while developing computational models for performance evaluation. His sustainable construction work applies Analytical Hierarchy Process to green building standards and investigates geopolymers using industrial byproducts like ferrochrome slag. Recent publications demonstrate urgent responses to Turkey's seismic events, particularly the 2023 Kahramanmaraş earthquakes. His 12 journal articles published between 2016-2025 show accelerating output after his PhD, with 7 papers in the last three years. International journals dominate his work (8 articles), primarily addressing earthquake engineering (Natural Hazards, Journal of Earthquake and Tsunami) and sustainable construction (Quality & Quantity). The 2023 Kahramanmaraş earthquakes catalyzed his most productive period, yielding three major studies on seismic performance evaluation, bibliometric analysis, and fault rupture characteristics. Dr. Varolguneş actively leads two nationally funded research projects: as principal investigator for seismic software comparison research and as collaborator on geopolymer development from industrial waste. He teaches core undergraduate courses including Reinforced Concrete High Structures and Construction Management, integrating his pre-academic industry experience with current earthquake engineering research to prepare students for practical challenges in Turkey's seismic landscape.

Abdulkadir YelmanView profile

Lecturer

• Blockchain Applications
• Smart Grids
• Electric Vehicle Technology
• +3 more

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
• +2 more

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 ARIKANView profile

Lecturer

• Textile Engineering
• Textile Sciences
• Yarn Technology
• +9 more

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.