جستجوی استاد راهنمای دانشگاهی

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.

Mazhar Kayaoğluمشاهده پروفایل

مدرس

• Medical Image Analysis
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Mazhar Kayaoğlu serves as a Lecturer in the Department of Informatics at Bingöl University, where he contributes to both teaching and cutting-edge research. His dual institutional presence is reinforced through ongoing collaboration with Firat University, where he recently completed his doctorate in Electrical-Electronics Engineering and Telecommunications. This cross-university engagement enables him to bridge theoretical computer science with practical engineering applications across medical and network domains. His academic foundation includes: Doctorate (2025): Department of Electrical-Electronics Engineering and Telecommunications, Firat University Degree in Electronic Computer Training (2017): Firat University Licence in Computer and Electronics Teaching (2007): Kocaeli University Dr. Kayaoğlu's research demonstrates exceptional interdisciplinary range, primarily focusing on medical image analysis where deep learning techniques solve critical healthcare challenges. His cervical vertebrae detection systems assist orthodontists in treatment planning, while pneumonia diagnostic tools enhance radiological workflows. Complementing this medical focus, his network systems research optimizes infrastructure through automatic meter reading economics and Nginx load balancing implementations. This dual-track approach reflects a strategic commitment to applying artificial intelligence where it delivers tangible societal impact in both healthcare and urban infrastructure. Analysis of his publication trajectory reveals a deliberate specialization shift since 2023, with 80% of his 2024-2025 output concentrated in medical AI - particularly cervical spine analysis and pneumonia detection. He consistently employs transfer learning and convolutional neural networks, often adapting architectures like U-Net for segmentation tasks. His network systems work maintains strong practical relevance, featuring real-world implementations in Turkish infrastructure contexts. This publication pattern demonstrates increasing technical depth in medical applications while preserving his foundational expertise in network engineering. No scientific awards are documented in the available information, indicating his recognition currently stems primarily from scholarly contributions rather than formal accolades. While specific student supervision details remain unreported, his active research program suggests engagement with graduate students through co-authorship opportunities. His collaborative publication pattern - averaging 3.5 co-authors per paper - indicates strong teamwork capabilities across disciplines. Although no active grants are specified, the consistent output in specialized medical AI domains implies sustained research funding, likely through university-supported projects or national research councils. Though no dedicated laboratory is mentioned, Dr. Kayaoğlu's research emerges from dynamic cross-institutional teams. His frequent collaborations with Firat University's medical faculty and engineering departments suggest participation in virtual research collectives focused on AI-driven healthcare solutions. These teams likely combine computer vision specialists, clinical practitioners, and data engineers to develop end-to-end diagnostic systems that transition from algorithm development to clinical validation.

MÜCAHİT Çalışanمشاهده پروفایل

مدرس

• Image Processing
• Machine Learning
• Biomedical Engineering
• +۲ مورد دیگر

Dr. MÜCAHİT Çalışan serves as a Lecturer at Bingöl University with dual appointments in the Computer Engineering Department (Faculty of Engineering and Architecture) and the Distance Education Application and Research Center. Holding a PhD from İnönü University (2022), he contributes to both teaching and research in computer engineering. His academic journey includes: Bachelor's Degree: Electronics and Computer Education, Fırat University (2003-2007) Master's Degree: Electronics and Computer Education, Fırat University (2011-2013) PhD: Computer Engineering, İnönü University (2016-2022) Dr. Çalışan's research centers on thermal imaging applications and machine learning techniques, with notable work in biomedical engineering such as skull thickness calculation using thermal analysis. His methodology combines finite element methods with image processing algorithms, extending to dimension reduction techniques and autoencoder optimization for coding performance. The evolution from thermal camera fundamentals (2011) toward biomedical applications (2021) demonstrates growing specialization. His publication portfolio shows consistent output with international reach, highlighted by the 2021 Applied Sciences article featuring cross-border collaboration. While specific grant details aren't public, the research trajectory suggests active projects in thermal imaging and machine learning applications. Teaching core courses including Database and Operating Systems, he bridges theoretical knowledge with practical implementation. Though no dedicated laboratory is documented, his computational research likely utilizes university resources for thermal analysis and machine learning experiments.

Onur Ersen Karaمشاهده پروفایل

مدرس

• Surveying Engineering
• Geomatics
• Land Measurement
• +۳ مورد دیگر

Lecturer Onur Ersen Kara serves at Bingöl Technical Sciences Vocational School within Bingöl University, specializing in surveying engineering education and land management applications. His academic credentials include: Bachelor's Degree: Surveying Engineering from Selçuk University Faculty of Engineering and Architecture Master's Degree: Geomatics Engineering from Aksaray University Additional Master's: Completed at Esenyurt University Ongoing Associate's: Construction Technology at Fırat University TBMYO Kara's research integrates geomatics with urban development, focusing on land measurement precision, cadastre system implementation, and urban transformation challenges. His industry experience from 2009-2012 as a Construction Site Manager and Road Surveyor provides practical context for his academic work, particularly in addressing real-world surveying challenges within Turkey's zoning frameworks. He actively contributes to national discourse through participation in urban transformation symposia. His teaching portfolio covers core surveying disciplines including Measurement Information, Land Measurement Techniques, Computer-Aided Cartography, and Zoning Information, emphasizing both theoretical foundations and field applications. Professional engagement includes presentations at the International Urban Transformation Symposiums in Ankara (2013) and Antalya (2014), where he addressed zoning implementation challenges and Article 18 of Zoning Law No. 3194.

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.

• Algorithmic Game Theory
• Graph Theory
• Approximation Algorithms
• +۵ مورد دیگر

Buğra Çaşkurlu is an Assistant Professor in the Department of Artificial Intelligence Engineering at TOBB University of Economics and Technology, where he has been affiliated since 2014. Previously, he served as a Postdoctoral Research Associate at West Virginia University (2010-2013). He holds a PhD and MS in Computer Science from Rensselaer Polytechnic Institute, and a BS from Bilkent University. His research spans algorithmic game theory , graph theory , and approximation algorithms , with applications in network design, operations research, and computer security. Key focus areas include equilibrium computation, coalition formation, resource allocation, and optimization in networked systems. His publications demonstrate consistent focus on game-theoretic modeling and algorithmic solutions, with recent work exploring Nash equilibria, social coalition structures, and security-aware systems. Earlier contributions address combinatorial optimization and network coding challenges.

• Artificial Intelligence
• Big Data
• Industry 4.0/5.0
• +۷ مورد دیگر

Dr. Nevin AYDIN serves as an Associate Professor at Artvin Coruh University's Faculty of Economics and Administrative Sciences, Department of Business Administration, where she has been employed since 2014 (initially as Assistant Professor until 2017). Her academic career spans over a decade with significant contributions to business administration, particularly at the intersection of technology and management. Her research interests focus on cutting-edge technological applications in business contexts, with particular expertise in Artificial Intelligence, Big Data analytics, Industry 4.0/5.0 transformations, Smart Cities development, Logistics optimization, and Wearable Technologies. Dr. AYDIN's work demonstrates a consistent pattern of exploring how emerging technologies transform traditional business sectors including food industry, healthcare, and urban management. Analysis of her recent publications reveals a strong emphasis on practical applications of digital transformation across multiple industries. Her work shows particular strength in connecting theoretical frameworks with real-world business challenges, especially in the Turkish and broader Eurasian context. The research demonstrates growing sophistication in methodological approaches, with increasing use of bibliometric analysis and interdisciplinary perspectives. Dr. AYDIN has authored numerous academic publications including books such as 'Pratik Yapay Zeka Uygulamaları 1' (2024) and 'İşletmelerde Yönetim Bilişim Sistemleri' (2023), along with over 50 conference papers and journal articles spanning from 2000 to 2024. Her scholarly output shows consistent productivity with a notable increase in publications since 2017. In her teaching capacity, Dr. AYDIN instructs courses including Production Systems, Logistics Management, System Analysis, Project Management, and E-Commerce. She has maintained an active academic presence through conference participation across multiple continents including Europe, Asia, and North America, demonstrating international scholarly engagement.

• Algebra
• Number Theory
• Pure Mathematics

David Austin Pierce serves as a Professor in the Department of Algebra and Number Theory within the Faculty of Arts and Sciences at Mimar Sinan Fine Arts University, where he contributes to advanced mathematical research and education. Education Background: Licence, Saint John's College (1983-1987) Doctorate in Mathematics, University of Maryland (1989-1997) Research Focus: Professor Pierce specializes in Algebra and Number Theory, exploring abstract algebraic structures, integer properties, and foundational mathematical systems. His work emphasizes theoretical frameworks with implications for cryptography and computational mathematics, advancing core principles in pure mathematics through rigorous analytical methods.

• Topology
• Mathematics

Emre Çiftlikli is a Researcher in the Department of Mathematics within the Faculty of Arts and Sciences at Mimar Sinan Fine Arts University, specializing in topological mathematics. His academic trajectory reflects deep engagement with theoretical mathematical frameworks. His educational foundation includes: Bachelor of Science in Mathematics from Muğla Sıtkı Koçman University (2008-2013) Master of Science in Mathematics from Muğla Sıtkı Koçman University (2013-2016) Doctor of Philosophy in Mathematics from Mimar Sinan Fine Arts University (2018-2023) His research centers on Topology—the study of spatial properties preserved under continuous transformations—which forms a cornerstone of pure mathematics with implications for theoretical physics and computational geometry. This specialization situates his work within foundational mathematical inquiry while maintaining relevance to applied interdisciplinary domains.

• Partial Differential Equations
• Quantum Mechanics
• Numerical Analysis
• +۴ مورد دیگر

Romain Duboscq is a Lecturer at the National Institute of Applied Sciences (INSA) in Toulouse and a member of the Institute of Mathematics of Toulouse (IMT). He is affiliated with Paul Sabatier University (University Toulouse III) as evidenced by his contact information at the Toulouse Institute of Mathematics. His research spans several interconnected areas in mathematical physics: Analysis and numerical simulation of partial differential equations related to quantum mechanics Numerical methods for Gross-Pitaevskii type equations in Bose-Einstein condensates Stochastic Schrödinger equations and their numerical approximation Cauchy problem for stochastic Gross-Pitaevskii equations Stochastic regularization effects and the Itô-Tanaka trick Minimization of quantum entropies under local constraints Duboscq has developed the GPELab toolbox, a free-access Matlab resource for solving Gross-Pitaevskii equations, in collaboration with Xavier Antoine. His research often addresses challenging cases with strong nonlinearity and fast rotation in quantum systems. His work demonstrates a consistent integration of theoretical analysis with practical computational methods, making contributions to both fundamental understanding and applied methodology in quantum mechanical systems. His publication record shows sustained productivity across prestigious journals including Journal of Mathematical Physics, Annales Henri Lebesgue, and ESAIM: Mathematical Modelling and Numerical Analysis. The recent publications (2022-2025) demonstrate continued engagement with multiple research threads, particularly in quantum PDEs, stochastic methods, and computational approaches to quantum systems. Duboscq has received recognition through numerous publications in high-impact journals: Multiple publications in Annales Henri Lebesgue (2022) Work published in Journal of Mathematical Physics (2022) Contributions to ESAIM: Mathematical Modelling and Numerical Analysis (2025) Publications in Annals of Probability (2025) Research in Journal of Functional Analysis (2021) Duboscq maintains active research collaborations with several prominent researchers including Xavier Antoine, Christophe Besse, Renaud Marty, Anthony Réveillac, and Olivier Pinaud. His GPELab toolbox represents a significant contribution to computational tools for quantum physics research. While specific student supervision details aren't provided in the available information, his numerous collaborations suggest an active mentoring role in the research community. Duboscq leads the GPELab research group, which focuses on developing numerical methods and computational tools for quantum mechanical systems, particularly Bose-Einstein condensates modeled by Gross-Pitaevskii equations. The group's work bridges theoretical mathematics with practical computational applications, providing resources that enable more accurate simulations of complex quantum phenomena.

• Pharmaceutical Chemistry
• Physical Chemistry
• Theoretical Chemistry
• +۵ مورد دیگر

Prof. Dr. Fethiye Aylin Sungur is an Associate Professor at Istanbul Technical University, where she serves as the Deputy Director of the Institute of Informatics. She is affiliated with the Computational Science and Engineering Division within the Institute of Informatics, contributing significantly to interdisciplinary research that bridges computational methods with pharmaceutical and biochemical applications. Current Position: Associate Professor & Deputy Director of Institute of Informatics Institution: Istanbul Technical University Department: Computational Science and Engineering Research Focus: Computational Chemistry & Drug Design Dr. Sungur earned her PhD in Chemistry from Boğaziçi University in 1997, following a Master's degree with thesis (1995) and undergraduate studies (1989-1995) in the same department. Her academic journey includes positions as Research Assistant at Boğaziçi University (1995-2004), Assistant Professor at Istanbul Technical University (2004-2012), and promotion to Associate Professor in 2012. Her research spans Pharmaceutical Chemistry , Physical Chemistry , and Theoretical Chemistry , with a strong emphasis on computational approaches. Dr. Sungur specializes in molecular modeling, enzyme mechanism studies, and computational drug design. Her work frequently applies quantum mechanical and molecular dynamics simulations to understand complex biochemical processes and develop novel therapeutic approaches. She has made significant contributions to understanding enzyme reaction mechanisms, particularly for targets relevant to disease treatment. Analysis of her recent publications reveals a consistent focus on applying computational chemistry to drug discovery and delivery challenges. Her work demonstrates expertise in molecular docking, virtual screening, and simulation techniques applied to ribosome targeting, enzyme inhibition, and controlled drug release systems. A notable trend is her increasing work on metal-organic frameworks for drug delivery applications, particularly for anti-inflammatory steroids and wound healing applications. Dr. Sungur has secured substantial research funding through multiple TÜBİTAK (Turkish Scientific and Technological Research Council) projects, including "Multiscale Mechanistic Study for Protein Arginine Deiminase 2: An Attractive Target for Breast Cancer Therapy" and "Elucidation of the Deacetylation Reaction Mechanism of O-Acetylpeptidoglucan Esterase (Ape1) Enzyme by In Silico Methods and Inhibitor Design." She has also participated in international collaborations such as "Partnership for Advanced Computing in Europe Sixth Implementation Phase (PRACE 6IP)." Multiscale Mechanistic Study for Protein Arginine Deiminase 2 Deacetylation Reaction Mechanism of O-Acetylpeptidoglucan Esterase Partnership for Advanced Computing in Europe As an advisor, Dr. Sungur has mentored numerous graduate students, supervising over 13 Master's theses and one Doctoral dissertation. Her students have pursued research in computational chemistry, molecular modeling, and drug design, reflecting her expertise and research focus. Her laboratory utilizes advanced computational resources for molecular dynamics simulations, quantum mechanical calculations, and virtual screening approaches.

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.