جست‌وجوی استاد و پژوهشگر

• Liver Pathology
• Liver Transplantation Pathology
• Hepatopancreatobiliary Pathology
• +۴ مورد دیگر

Ayşe Armutlu, M.D. is an Attending Physician and Specialist in the Department of Pathology at Koç University since 2016. She completed her medical education and pathology residency at Gazi University Faculty of Medicine (2002–2014) and advanced training in liver pathology at Indiana University (2018). Her clinical focus includes Liver Pathology , Hepatopancreatobiliary Pathology , and Uropathology . Medical Doctorate , Gazi University School of Medicine (2002–2009) Medical Pathology Residency , Gazi University Department of Medical Pathology (2009–2014) Observer in Pathology , Indiana University Department of Pathology (2018) Her research spans prostate cancer staging , pancreatic tumor subtyping , and hepatic pathology , with over 20 publications since 2016. Key studies include PSMA PET/CT applications , duct-centric Whipple specimen analysis , and metaplastic pancreatic carcinomas . While no scientific awards are explicitly documented, her work emphasizes imaging-pathology integration and novel diagnostic protocols . She has no known part-time affiliations and no appointments are listed in the scraped data.

Deniz Yuretمشاهده پروفایل

استاد

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

Deniz Yuret is a Professor in the Department of Computer Engineering at Koç University , Istanbul, and the founding director of the KUIS AI Center . Previously, he spent 12 years at the MIT AI Lab and co-founded Inquira, Inc. His research focuses on Natural Language Processing and Machine Learning , with significant contributions in dependency parsing , language modeling , grounded language learning , and character-level NLP . He has pioneered frameworks like Knet , a deep learning library in Julia, and AutoGrad.jl for automatic differentiation. Deniz's academic work spans neural architectures for language-robot interaction, transfer learning in low-resource NMT, and context embeddings for grammatical category acquisition. His recent publications emphasize transformer models , multimodal systems , and efficient language modeling . He has supervised multiple graduate students, including Emre Can Açıkgöz (PhD, UIUC), Onur Kuru (M.S. 2016), Saman Zia (M.S. 2016), and Osman Baskaya (M.S. 2015). His projects include the TUBITAK 1001 (2016-2018) and ReGROUND (2015-2018) in collaboration with international institutions.

Ali Emre Turgutمشاهده پروفایل

دانشیار

• Swarm robotics
• mechatronics
• manufacturing systems
• +۳ مورد دیگر

Ali Emre Turgut is an Associate Professor at Middle East Technical University (METU) in Ankara, Turkey. His research intersects robotics, control systems, and bio-inspired design, with a focus on swarm robotics, UAVs, and complex systems. He maintains a formal email address ( aturgut@metu.edu.tr ) and an online presence at users.metu.edu.tr/aturgut . Education B.Sc. in Electrical Engineering, METU (1996) M.Sc. in Electrical Engineering, METU (1999) Ph.D. in Electrical Engineering, METU (2008) Research Interests center on swarm robotics , mechatronics , and unmanned aerial vehicles (UAVs) . His work explores self-organization in robotic swarms, bio-inspired control mechanisms, and adaptive systems for complex environments. Key themes include: Swarm intelligence for collective motion and task specialization Design and control of aerial and legged robots Applications in environmental monitoring, manufacturing, and biological interaction Publication Trends highlight his leadership in swarm robotics, with recent works addressing predictive flocking algorithms, biohybrid platforms, and exoskeleton-assisted motor learning. His studies often integrate hardware design with computational models. Advising and Grants information is unavailable in the provided texts, though his active research role since 2008 suggests significant contributions to graduate training and funded projects in robotics.

• 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.

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.

• Physiotherapy
• Rehabilitation
• Telemedicine
• +۴ مورد دیگر

Şeyda Ercan Yüceer serves as a Research Assistant at the Department of Physiotherapy and Rehabilitation within the Faculty of Health Sciences at Muğla Sıtkı Koçman University, Turkey, and holds concurrent affiliation with the Institute of Health Sciences at the same institution. Her academic credentials include: Bachelor's degree in Physiotherapy and Rehabilitation from Bolu Abant İzzet Baysal University, Kemal Demir School of Physical Therapy and Rehabilitation (2012-2016) Master's degree (MSc) in Physiotherapy and Rehabilitation from Süleyman Demirel University, Institute of Health Sciences (2017-2020) Ongoing doctoral studies in Physiotherapy and Rehabilitation at Muğla Sıtkı Koçman University, Institute of Health Sciences (2020-present) Her research spans telemedicine applications, AI integration in rehabilitation, geriatric physiotherapy, pelvic functional anatomy, and pandemic-related physical activity impacts. Recent publications demonstrate consistent focus on technology-enhanced rehabilitation methodologies and pandemic health consequences, with increasing emphasis on AI-driven solutions and specialized clinical applications since 2020. Her work bridges traditional physiotherapy with digital innovation, particularly in neurological rehabilitation and geriatric care. Dr. Yüceer has contributed as a researcher to three significant national projects: the 1st National Trakya University Physical Activity Symposium (2020-2021), Supporting Neurological Rehabilitation Through Technology-Based Methods (2019-2021), and the 1st International Balkan Prosthetics and Orthotics Symposium (2019-2020). These projects reflect her commitment to advancing rehabilitation science through technological integration and interdisciplinary collaboration. Her scholarly output extends to book chapters and translations that enhance educational resources in proprioceptive neuromuscular facilitation, geriatric rehabilitation principles, and pelvic anatomy, demonstrating active knowledge translation within the physiotherapy community.

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.

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.