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• Machine Learning
• Data Mining
• Educational Technologies
• +7 more

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.

Éva GalambosView profile

Associate Professor

• Art Conservation
• Restoration Science
• Polarization Microscopy
• +4 more

Éva Galambos DLA is an Associate Professor and Laboratory Manager at the Hungarian University of Fine Arts' Department of Restoration since 2014, promoted to Associate Professor in 2023. She serves as head of the microscopy laboratory and teaches materials science and polarization microscopic examination of inorganic pigments. Her research focuses on art conservation science , specializing in polarization microscopy of inorganic pigments , material analysis of cultural heritage objects , and diagnostic techniques for restoration . She developed Hungary's first digital pigment database ( pigmentum.hu ) and established advanced analytical laboratories through significant research grants. Galambos has led material investigations for major museum projects including the Museum of Fine Arts' Gamhudi coffin collection, Buda Castle Gothic sculptures, and medieval wall paintings across Hungary and Transylvania. Her work bridges conservation practice with scientific analysis through collaborations with ELTE, MTA research institutes, and international partners. Kerényi-pályázat nívódíj (1994) Köztársasági ösztöndíj (1998-1999) Erasmus ösztöndíj (1999) MAOE alkotói ösztöndíj (2001, 2008) As a doctoral supervisor, she has guided 11 completed DLA dissertations focusing on pigment analysis, forgery detection, and historical techniques. Her laboratory serves as a national hub for conservation science, training specialists in microscopic analysis and material diagnostics for cultural heritage preservation.

• Computer Vision
• Image Analysis
• Machine Learning
• +4 more

Dr Shahana Bano is a Lecturer in the School of Computing, Engineering & Technology at Robert Gordon University, specializing in interdisciplinary applications of Artificial Intelligence. Her research spans biomedical imaging, environmental monitoring, infrastructure analytics, and socio-technical systems through the Machine Vision Research Group and Cybersecurity Research Group. Her educational background includes a PhD in Computer Science and Engineering, M.Tech in Computer Science and Engineering, MSc in Information Systems, and BCA - all completed full-time. Her research philosophy centers on convergence, bringing together diverse data types, technologies, and disciplines to create impactful, adaptive systems that bridge academic innovation with societal relevance. Dr Bano's research interests focus on Computer Vision, Image Analysis, Machine Learning, Data Analytics, Internet of Things, Text to Speech Systems, and Social Media Threat Intelligence. Her recent work demonstrates strong application of these interests to medical diagnostics (CAR-T cell classification), environmental monitoring (geothermal reservoir modeling), infrastructure analytics (pipeline defect detection), and social systems (hate detection in football communities). Her publication record shows consistent output with 32 research outputs from 2015-2025, demonstrating increasing focus on medical and environmental applications of AI in recent years. The work spans theoretical computer vision advancements to practical implementations addressing UN Sustainable Development Goals. Associate Fellow (AFHEA) 2023 from Advance HE Dr Bano actively supervises PhD students and mentors interns on diverse projects. Current PhD supervision includes research on morphological classification of CAR-T cell images for leukemia diagnosis and acoustic emission-based pipeline defect detection. She also guides students on projects involving AR-based navigation, NDVI vegetation mapping, hate detection in football communities, multimodal sensor fusion, and airport runway object detection. Her lab resources are supported through university research groups and collaborations focused on machine vision and cybersecurity applications.