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نمایش ۴۶-۶۰ از ۱٬۱۹۴ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
استادیار
Dr. İsmail Arı is an Assistant Professor in the Computer Science department at Özyeğin University . He holds a PhD from the University of California, Santa Cruz (2004), MS from University of Maryland (2000), and BS in Electrical & Electronics Engineering from Boğaziçi University (1998).
دانشیار
Assoc. Prof. Dr. Adem YOLCU is an active faculty member at Kafkas University's Faculty of Arts and Sciences, Department of Mathematics, specializing in advanced topological structures with applications in decision-making systems. Holding a PhD in Mathematics from Kafkas University (2020), he has established himself as a leading researcher in fuzzy topology and soft set theory. PhD in Mathematics (2020), Kafkas University Master's in Mathematics (2016), Kafkas University Bachelor's in Mathematics (2014), Kafkas University His research focuses on the intersection of topology, fuzzy logic, and decision theory, particularly exploring neutrosophic soft sets, hypersoft topological spaces, and their applications in multi-criteria decision-making problems. His work bridges theoretical mathematics with practical computational applications in risk assessment and building safety analysis. Recent publications demonstrate a consistent trajectory in developing novel frameworks for fuzzy parameterized systems, with 15+ articles published between 2019-2024 in SCI/ESCI-indexed journals. His work shows particular strength in extending classical topological concepts to neutrosophic and Pythagorean fuzzy environments. As an academic advisor, he has supervised Master's research including Büşra Aka's thesis on neutrosophic soft multisets. His collaborative network spans international researchers including Taha Yasin Öztürk (60+ joint publications), Florentin Smarandache, and Sadık Bayramov. His research group focuses on computational topology applications, with particular emphasis on developing mathematical frameworks for uncertainty handling in decision support systems. Current projects include hypersoft set applications in sustainable security systems and Fermatean fuzzy topological structures.
استادیار
Sanem Kabadayı is an Assistant Professor at the Department of Computer Engineering, Istanbul Technical University. Her research focuses on sensor networks, middleware frameworks, and pervasive computing. Research Interests Sensor Networks (Wireless, Ad-hoc, Heterogeneous) Pervasive and Ubiquitous Computing Middleware Design for Smart Environments Data Abstraction and Communication Paradigms Advisory Role Advisor for Yakup Kayatas' thesis on AI-assisted IoT agents for smart spaces (2025). Recent Research Trends Her 15 most recent publications (2006–2024) emphasize sensor network architectures, middleware innovations for programmable environments, and abstractions for heterogeneous sensor integration. Key themes include AI-driven IoT agents, positioning techniques in wireless networks, and virtual sensor frameworks.
Prof. Dr. Selcuk Paker is a faculty member at the Department of Electronics and Communication Engineering , Faculty of Electrical and Electronics Engineering , Istanbul Technical University. His research spans electromagnetic field theory, microwave systems, and telecommunications, with a focus on antenna design, radar imaging algorithms, and bioelectromagnetics. Research Interests : Electromagnetic scattering, inverse scattering, radar systems, SAR imaging, GNSS algorithms, microwave heating, and wireless communication. Recent publications highlight his work in 5G antenna design , radar-based earthquake detection , and biological effects of RF exposure . He contributes to microwave and radar technologies, including applications in structural diagnostics and sensor networks.
استادیار
Onur KARDEŞ serves as Assistant Professor in the Department of Computer Engineering at Beykent University's Faculty of Engineering and Architecture since 2020. His prior academic appointments include: Research Assistant, Department of Computer Science, Stevens Institute of Technology (2004-2008) Lecturer, Department of Mathematics and Computer Science, Faculty of Arts and Sciences, Beykent University (2000-2004) His research integrates data mining, privacy-preserving computation, and artificial intelligence with practical applications in educational technology and urban systems. Key contributions include developing privacy-enhancing protocols for distributed data mining and pioneering generative AI solutions for automated student assessment and digital teaching assistants. Analysis of his 2023-2025 publications reveals accelerating focus on generative AI implementations, particularly in educational evaluation (automated examination paper analysis) and urban planning (AI-driven smart city frameworks). This evolution demonstrates strategic adaptation to emerging technologies while maintaining core expertise in secure computation and data mining.
استادیار
Betül Boz is an Assistant Professor at the Department of Computer Hardware, Faculty of Engineering, Marmara University. She holds a B.Sc. and M.Sc. in Computer Engineering from Marmara University, and a Ph.D. in Computer Engineering from Boğaziçi University. Her research focuses on computer architecture, optimization, and evolutionary computing. B.Sc., M.Sc., and Ph.D. in Computer Engineering Her research interests include computer architecture, parallel algorithms, optimization techniques, and evolutionary algorithms applied to graph coloring and scheduling. Recent work explores cloud computing scheduling, register allocation, and bioinformatics applications like circRNA-disease prediction. She has published extensively in these areas, utilizing evolutionary computing and machine learning. Key trends in her publications include evolutionary algorithms for graph coloring (2015–2025), register allocation (2004–2024), and cloud computing optimization (2023). She also investigates biomedical applications such as circRNA-disease association prediction. She has advised one thesis, managed one project, and her work aligns with UN Sustainable Development Goals. Her research outputs include 14 WoS-indexed publications, 11 WoS citations, and an h-index of 25 on WoS.
Dr. Gözde Damla Turhan is a Researcher at the Department of Architecture within the Faculty of Fine Arts and Design at İzmir University of Economics, a position she has held since September 2017. She holds a B.Sc. in Architecture from İzmir Ekonomi Üniversitesi (2014), followed by dual Master's degrees: M.Arch in Advanced Architectural Design (2016) and M.Sc. in Architecture (2016). Her Ph.D. in Design Studies (2022) focused on biobased materials, computational design, and digital fabrication. Current research interests include AI applications in design (machine learning, diffusion models, LLMs), and sustainable material innovation. Her work bridges architecture and computational technologies, emphasizing bio-based materials (e.g., bacterial cellulose), digital fabrication methods, and AI-driven design processes. She has explored topics like urban rehabilitation via GANs, NFT art hybrid experiences, and life cycle assessments of unconventional construction materials. Publications (2016–2023) span computational form-finding, material science, and digital tools in architecture. She actively contributes to design pedagogy, investigating how AI tools like diffusion models can reshape educational frameworks.
Erdinç Altuğ serves as a Professor in the Department of Mechanical Engineering at Istanbul Technical University, specializing in advanced aerial robotics and control systems. His work bridges theoretical control methodologies with practical UAV applications. Research interests focus on Unmanned Aerial Vehicle design and fault tolerance Quadcopter dynamics and vertical takeoff systems Adaptive control for parametric variations Rapid prototyping of hybrid VTOL platforms His recent publications demonstrate consistent innovation in autonomous flight systems, particularly in fault-tolerant operational modal analysis and modular multi-drone configurations. Current projects include: Hibrit İnsansız Hava Aracı Ile Otonom Teslimat Sistemi Geliştirilmesi (TUBITAK, 2020-2022) Mini Jet Motorlu Dikine Kalkıp İnebilen Otonom Taşıyıcı Robot Geliştirilmesi (TUBITAK, 2018-2021) Kampüs içi ve bina içi ortamlarda çalışacak otonom taşıma aracı algoritmaları (SRP, 2018-2021) Supervising 26 graduate works, his research impacts both academic and industrial UAV development.
استادیار
Veysi Başhan serves as an Assistant Professor in the Department of Marine Engineering within the Faculty of Naval Architecture and Ocean Engineering at Istanbul Technical University (ITU). His academic profile demonstrates active engagement in maritime engineering research with current publications extending through 2025 and an active research project on hybrid renewable energy systems analysis. Professor Başhan's research spans critical maritime engineering domains with particular emphasis on renewable energy integration, risk assessment methodologies, and marine propulsion systems. His work innovatively combines fuzzy logic, Bayesian networks, and multi-criteria decision-making approaches to address complex challenges in maritime operations, energy systems, and safety protocols. This interdisciplinary approach bridges traditional marine engineering with modern computational techniques for risk analysis and system optimization. His publication portfolio reveals a clear trajectory toward sustainable maritime technologies, with increasing focus on wind-solar hybrid systems, alternative fuels like methanol, and autonomous navigation reliability. The research demonstrates consistent application of fuzzy-based analytical frameworks across diverse maritime contexts from engine performance to ballast water treatment systems. Current research activities include the 2024 project "Hibrit Yenilenebilir Enerji Sistemlerinde Arızaların Analizi ve Çözüm Önerileri" (Analysis of Failures in Hybrid Renewable Energy Systems and Solution Proposals), indicating ongoing commitment to solving practical engineering challenges in renewable energy integration for maritime applications. His scholarly impact is evidenced by 32 research outputs, 366 Scopus citations, and an h-index of 9.
ZİYATTİN TAŞ is a Lecturer in the Mathematics Department at the Faculty of Arts and Sciences, Bingöl University. He holds a Ph.D. in Mathematics from Yüzüncü Yıl University (2005) after completing his M.Sc. at Harran University (1995) and B.Sc. at Yüzüncü Yıl University (1993). His research focuses on functional analysis, Banach spaces, graph theory, and topological descriptors. He has published extensively in international journals like Journal of Discrete Mathematical Sciences & Cryptography and Graphs and Linear Algebra . Educations: B.Sc. (1993), M.Sc. (1995), Ph.D. (2005) Research interests include metric geometry, topological indices of molecular structures, and mathematical properties of graphs. His recent work involves analyzing entropy measurements in hexagonal cycloarene structures and domination connectivity in paths/cycles. He has collaborated on studies applying topological descriptors to Remdesivir drug design and silicate carbide analysis. Over 20 peer-reviewed articles, including contributions to QSPR analysis of octanes and Petersen graph topological correlations. No explicit awards listed, but active in national/international conferences since 2007.
دانشیار
Nurcan Tunçbağ serves as an Associate Professor at Koç University, holding a joint appointment between the Department of Chemical and Biological Engineering and the School of Medicine. Her academic career spans significant contributions to computational biology and bioinformatics, with prior experience including a post-doctoral fellowship at MIT and a faculty position at Middle East Technical University from 2014 to 2021. Her educational background is rooted in engineering and computational sciences: PhD in Computational Sciences and Engineering, Koç University (2010) MS in Computational Sciences and Engineering, Koç University (2007) BS in Chemical Engineering, Istanbul Technical University (2005) Research Interests: Dr. Tunçbağ's research program centers on computational systems biology, leveraging network-based approaches to understand complex biological systems. Her work encompasses network medicine, multi-omic data integration, and the analysis of single-cell and bulk omic datasets to uncover latent cancer driver mutations. She develops computational models for network reconstruction and applies these to drug design and disease mechanism elucidation, bridging engineering principles with biomedical challenges. Scientific Awards: Her impactful research has been recognized with several prestigious awards: TÜBİTAK Incentive Award (2021) UNESCO-L'Oreal International Rising Talent Award (2019) TÜBİTAK Young Scientist Award TÜBA Young Scientist Award TÜSEB Young Scientist Award BA Young Scientist Award Professional Affiliations: Since 2020, Dr. Tunçbağ has been an active member of the Global Young Academy, and she joined the Mediterranean Science Team in 2022. Information regarding her graduate student advising, research grants, and laboratory teams was not available in the provided sources.
Cavit Fatih Küçüktezcan is an Assistant Professor in the Department of Electrical Engineering at Istanbul Technical University, College of Engineering. His research focuses on power system security, optimization methods, and smart grid technologies. He actively contributes to advancements in electric vehicle energy systems, battery modeling, and resilience of renewable-rich power grids. Research Interests: His work spans power system dynamic security , preventive and corrective control , heuristic and evolutionary optimization (e.g., differential evolution, mean-variance mapping, genetic algorithms), and the application of machine learning for transient stability prediction. He also investigates electric vehicle battery systems , including optimal cell selection and real-time energy consumption modeling. The publication trends show a shift toward data-driven and AI-enhanced approaches in power systems, especially in modeling cyber-attack impacts and improving grid resilience. His recent articles emphasize practical applications in sustainable transportation and secure grid operation under uncertainty. Scientific Contributions: Developed optimization frameworks for preventive control with search space reduction. Applied mean-variance mapping optimization to enhance dynamic security. Explored machine learning benchmarks for transient stability under cyber threats. Contributed to battery modeling and energy efficiency in electric buses. Advising and Grants: While specific details on students or funded projects are not available in the provided text, his collaborative research patterns suggest active supervision and team-based research in power systems and energy technology. He frequently co-authors with researchers from Istanbul Technical University, indicating strong institutional collaboration. Labs and Teams: Though no specific lab or research group is named, his work aligns with smart grid, energy systems, and optimization research teams within the Department of Electrical Engineering at ITU. His focus on real-time data and cyber-physical systems suggests potential involvement in intelligent grid monitoring and control initiatives.
Tamer Ölmez is a Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University (ITU), College of Engineering, where he conducts cutting-edge research in biomedical signal processing, brain-computer interfaces (BCI), and deep learning applications in medical systems. His work bridges engineering and neuroscience, with a strong focus on EEG-based motor imagery classification, medical image analysis, and embedded deep learning systems. His research interests include motor imagery EEG signal processing , brain-computer interfaces , feature extraction , deep neural networks , classification algorithms , and medical image analysis . He applies machine learning and signal processing techniques to improve diagnostic accuracy and system performance in neuroengineering and healthcare technologies. The recent publications highlight a consistent trend in leveraging divergence-based deep neural networks , convolutional neural networks , and small-sized models for efficient and accurate classification in BCI and medical imaging. His work emphasizes performance improvement with reduced channel counts, noise elimination, and real-time applicability in embedded systems. Scientific Awards: Excellent Oral Presentation Certificate, June 1, 2015 Advising and Grants: He is actively supervising 26 theses in progress, indicating a strong mentoring role. He has led multiple funded research projects, including those funded by ITU’s Technology Transfer Office (TTO) and Scientific Research Projects (BAP), such as 'Classification of Medical Images with Deep Learning Method in Embedded Systems' and 'New Approaches to Finding Optimal Protein Folding'. Labs and Research Teams: While specific lab names are not mentioned, his collaborative fingerprint and project leadership suggest he leads or is a key member of a research group focused on biomedical signal processing, neural networks, and intelligent systems at ITU.
استادیار
Beyza Eken serves as Assistant Professor in the Department of Software Engineering at Sakarya University's Faculty of Computer and Information Sciences, teaching core courses including Software Project Management, Natural Language Processing, and Graduation Projects while maintaining active research in software engineering and AI applications. Her academic credentials include: Doctorate in Computer Engineering from Istanbul Technical University (2015), thesis: "Software Defect Prediction" Master's in Computer Engineering from Istanbul Technical University (2011-2015), thesis: "Entity Name Recognition in Short Texts" Bachelor's in Computer Engineering from Sakarya University (2007-2011) Dr. Eken's research integrates machine learning with software engineering, specializing in defect prediction models that incorporate personalized developer factors and industrial deployment challenges. Her work bridges natural language processing for Turkish social media analysis with software quality assurance, demonstrating expertise in both theoretical modeling and practical implementation in industrial settings. Recent expansions include neuro-symbolic AI for test oracle generation and MLOps frameworks. Publication trends reveal consistent focus on empirical software engineering from 2018-2021 (defect prediction, community smells, industrial deployment), evolving into cutting-edge domains by 2023-2025 (neuro-symbolic testing, employee feedback analysis, MLOps). Her work shows strong industry-academia collaboration patterns with increasing methodological sophistication. Dr. Eken actively contributes to academic service as reviewer for ACM Transactions on Software Engineering and Methodology (2024) and IEEE Transactions on Software Engineering (2023). She leads research projects including "Developer-specific error prediction modeling" (2020) and the Mevlana exchange project with Ryerson University on data mining for defect prediction (2018), while supervising graduation projects and research area courses that develop student expertise in software engineering practices. Her international research engagement includes participation in the ASTERIx project at Università della Svizzera Italiana's Software Testing and Analysis Research Group (2023), demonstrating ongoing commitment to global collaboration in software engineering advancements.
Professor AYTAÇ GÜVEN is a faculty member at Gaziantep University's College of Engineering, Department of Civil Engineering, specializing in Fluid Mechanics and Numerical Modeling . With a PhD from Gaziantep University (2008), he progressed from Research Assistant (2001-2008) to Professor (2017). His research focuses on Hydrology , Climate Change Impact on water resources, Dam Safety , and Hydropower Assessment using Genetic Programming and Neural Networks . He served as Department Head (2020-present) and Vice Head (2009-2014). Education: PhD (Civil Engineering, Gaziantep University, 2008) MS (Civil Engineering, Gaziantep University, 2005) BS (Civil Engineering, Gaziantep University, 2000) His research interests span: Climate change adaptation in water resources Advanced numerical modeling for hydraulic structures Hydropower potential assessments Scour and sediment yield prediction Machine learning applications in hydrology Dam failure risk analysis His 57 peer-reviewed publications (including 2 books) emphasize hybrid modeling techniques, with recent work on CMIP6 climate scenarios , steppe spillways , and dam safety tools . He has advised 5 PhD and 21 Master's theses. Scientific awards include: 2024 Stanford Career Impact Award 2018 Best PhD Thesis (Baraj Güvenliği Derneği) 2016 Gaziantep University Science Award 2010 Best Master's Thesis (Baraj Güvenliği Derneği) 2018 Best Presentation (International Academic Association)
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