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Assoc. Prof. Dr. Sema Alaçam Doğan has been affiliated with Istanbul Technical University since 2014, serving as an Associate Professor in the Department of Architecture . She has held administrative roles including Deputy Head of Department and Erasmus Coordinator. Education : PhD in Informatics in Architectural Design (2008-2014), MS in Informatics in Architectural Design (2005-2008), and BS in Architecture (1999-2005) from Istanbul Technical University. Her research explores Computational Design , Artificial Intelligence in Architecture , and Sustainable Material Innovation . She investigates digital tools for heritage preservation, daylight optimization in BIM, and cognitive development in architecture students. Recent publications analyze AI-assisted design literacy , machine learning for Sinan mosques , and environmental comfort in Harran houses . Her work integrates algorithmic frameworks with sustainable practices. Scientific awards include multiple ITU Publication and Performance Awards (2021-2024), FABFEST Prizes , and the 2024 Artemis Educator Award from NASA. Active projects like "Physical Computation in Architectural Drawing" and "Robotic Fabrication with Recycled Wind Turbine Blades" demonstrate her leadership in computational and sustainable research.

• Computational Design
• Architectural Education
• Artificial Intelligence in Architecture
• +9 more

Fatih Ecevit is Full Professor of Mathematics at Boğaziçi University, serving as Vice Chair of the Mathematics Department. Former research associate at Max-Planck-Institut für Mathematik in den Naturwissenschaften, Leipzig (2005-2007). Research develops computational methods for high-frequency scattering problems, including: Boundary element methods for wave propagation Asymptotic analysis of scattering phenomena Galerkin formulations for integral equations Lattice sum evaluations in graph theory Principal investigator for TÜBİTAK-funded project: 'Hybrid integral equation methods for high-frequency scattering problems' (2017-2020). Teaches graduate and undergraduate courses in numerical analysis, partial differential equations, and real analysis.

• Numerical Analysis
• Partial Differential Equations
• Scattering Theory
• +2 more

Onur Varol is an Assistant Professor at Sabanci University's Computer Science Department and leads the VIRAL Lab, which focuses on computational social science, network science, and machine learning. He has affiliations with the Center of Excellence for Data Analytics. His research spans social bot detection, misinformation analysis, and online behavior modeling.

• Computational Social Science
• Network Science
• Machine Learning
• +4 more

Cem Say is a Professor in the Department of Computer Engineering at Boğaziçi University's Faculty of Engineering, where he has established himself as a leading researcher in theoretical computer science and artificial intelligence. His academic journey began with the completion of his doctoral dissertation titled Qualitative System Identification in 1992, which was the first thesis of Boğaziçi University's Computer Engineering PhD program. Professor Say's research interests span multiple domains of computer science, with significant contributions to quantum computing, artificial intelligence, and theoretical computer science. His early work focused on qualitative reasoning and simulation, particularly through the QSIM algorithm, where he made significant improvements to filtering techniques and addressed challenges in representing physical systems. Over time, his research evolved toward quantum computation, where he has made substantial contributions to quantum finite automata theory, space-bounded quantum computation, and quantum complexity classes. His recent work explores the energy complexity of computation, bridging theoretical computer science with thermodynamics. His publication record shows a clear evolution from classical AI and qualitative reasoning toward quantum computation. The most recent articles demonstrate his focus on space-bounded quantum computation, energy complexity of regular languages, and interactive proof systems with minimal resources. His work consistently addresses fundamental questions about computational limits, particularly in quantum and sublogarithmic-space models. Professor Say has also made significant contributions to science communication through several books written for general audiences, including 50 Soruda Yapay Zekâ (2018), Yeni Dünya, Yeni Ağ (2020), and En Hakiki Mürşit (2021), which explain complex concepts in artificial intelligence and scientific methodology in accessible terms. Throughout his career, Professor Say has been actively involved in the Turkish academic community, editing proceedings for multiple Turkish symposia on artificial intelligence and neural networks. His doctoral dissertation established foundational work in qualitative system identification, and his subsequent research has consistently pushed boundaries in theoretical computer science, particularly in quantum computation where he has collaborated extensively with Abuzer Yakaryılmaz and other researchers.

• Artificial Intelligence
• Quantum Computing
• Theoretical Computer Science
• +3 more

Başar Öztayşi is a Professor at the Department of Industrial Engineering , Istanbul Technical University , with expertise in fuzzy logic, multi-criteria decision making, and decision science. He has held administrative roles including Associate Professor (2017–present), Deputy Director of the Institute (2016–2017), and Assistant Professor (2013–2017). Fields of Study : Fuzzy Logic, Multi-criteria Decision Making, Decision Science Contact : oztaysib@itu.edu.tr , +90 212 293 1300 Research Interests focus on applying fuzzy set theory to complex decision problems, including financial management, risk assessment, and smart city energy systems. His work extends to industry 4.0 applications and process mining in e-commerce. Recent Publications (2024) analyze fuzzy approaches in financial management, risk assessment, and Industry 4.0, with subfields spanning bibliometric trends, allocation optimization, and sustainable energy planning. Earlier works explore AHP matrix consistency, file distribution models, and customer segmentation. Awards : Best Paper Award, FLINS 2018 Science - Art Awards

• Fuzzy Logic
• Multi-criteria Decision Making
• Decision Science
• +3 more

Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.

• Electromagnetics
• Microwave Engineering
• Antenna Technologies
• +3 more

Professor Vakur B. Erturk is a distinguished faculty member in the Department of Electrical and Electronics Engineering at Bilkent University's Faculty of Engineering. With a PhD from The Ohio-State University (2000), his academic journey spans over two decades of impactful research and teaching. His research focuses on advanced computational electromagnetics, specializing in closed-form Green's function representations, conformal antenna design, structural health monitoring systems, and metamaterial applications. His work bridges theoretical electromagnetics with practical engineering solutions, particularly in wireless sensing and high-frequency electromagnetic analysis. Professor Erturk's publication record demonstrates consistent innovation, with recent work emphasizing efficient computational methods like the multilevel fast multipole algorithm (MLFMA) for multiscale electromagnetic problems. His research shows strong continuity in antenna theory while expanding into metamaterial-inspired sensors and structural monitoring systems. Best master thesis award (1996) He actively mentors graduate students, with over 30 PhD and MSc graduates who have contributed significantly to fields including computational electromagnetics, antenna design, and wireless sensor development. His research group maintains strong collaborations with institutions like Middle East Technical University and researchers in metamaterials and structural health monitoring. Professor Erturk teaches core courses including Microwave Engineering, Antenna Engineering, and Computational Methods in Electromagnetics, shaping the next generation of electrical engineers through rigorous theoretical and practical instruction.

• Computational Electromagnetics
• Antenna Engineering
• Structural Health Monitoring
• +5 more

Prof. Dr. Özlem İlk Dağ is a Professor of Statistics at the Middle East Technical University (METU), Ankara, Turkey. She holds the position of Department Head of Statistics and serves on advisory boards for TUBITAK and the Journal of Biostatistics. Her academic journey includes roles from Research Assistant (1997) to Professor (2018), with affiliations in Actuarial Sciences and Biostatistics. Education: Ph.D. in Statistics (Iowa State University, 2004), M.S. and B.S. from METU. Research focuses on longitudinal data analysis, multilevel modeling, Bayesian methods, and biostatistics. She authored three editions of R Yazilimina Giris and a foundational book on multivariate longitudinal data analysis. Key contributions include developing marginalized transition random effects models (MTREM) and R packages like 'mmm'. Awards include METU's 20-year service recognition and teaching excellence. She has supervised numerous research projects and co-authored over 50 peer-reviewed articles across biostatistics, genomics, and statistical computing. Her work bridges statistical theory and application, with notable contributions to gene expression clustering, maternal antibody studies in veterinary science, and computational methods for longitudinal data. She maintains active collaborations in genomics and biostatistics, and her lab focuses on integrating statistical computing with biomedical research.

• Longitudinal Data Analysis
• Multilevel Modeling
• Interactive Graphics
• +5 more

Tayfun Günel is a Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University (ITU) , Faculty of Electrical and Electronics Engineering. He holds a PhD (1993), MSc (1988), and BSc (1986), all from ITU. His research spans microwave circuits, radar systems, antennas, and optimization using genetic algorithms and soft computing. His research interests include Microwave Circuits , Radar and Antennas , Optimization , and Genetic Algorithms . His work focuses on impedance matching, microstrip antennas, noise modeling, and metamaterial-based microwave components. He has taught courses such as Electromagnetic Fields, Radar Systems, and Satellite Communication Systems. The recent publications reflect a strong trend in microwave circuit design , antenna miniaturization , and the application of evolutionary algorithms (genetic algorithms, PSO) and machine learning (neural networks, SVR) in electromagnetic design and optimization. There is a consistent focus on practical microwave components like transmission lines, patches, and amplifiers, often using nanomaterials (e.g., carbon nanotubes) and metamaterials . His work bridges theoretical modeling with computational optimization for real-world RF and radar applications. Email: gunelmur@itu.edu.tr Professor Günel has supervised 2 completed PhD theses, 2 ongoing PhD theses, 23 completed master's theses, and 1 ongoing master's thesis, demonstrating a significant contribution to student mentoring. There are no specific grants or funding sources mentioned in the provided text. He is affiliated with research in microwave systems and antenna design , likely operating within the broader research ecosystem of the Electronics and Communication Engineering Department at ITU, which includes labs such as the Microwave Systems and Antennas Laboratory and the Radar and Microwave Technologies Research Laboratory.

• Microwave Circuits
• Radar Systems
• Antennas
• +12 more

Ozgur S. Oguz is an Assistant Professor at Bilkent University , Faculty of Computer Engineering, and the lead of the Learning for Intelligent Robotic Agents (LiRA) Lab . His research focuses on enhancing autonomous agents' capabilities in learning, reasoning, and planning, particularly for robotics applications. Education : PhD in Computer Science from TU Munich , studies at University of British Columbia (UBC) and Koç University , postdoctoral work at University of Stuttgart and Max Planck Institute for Intelligent Systems . His research explores algorithms for autonomous decision-making, with emphasis on deep learning , reinforcement learning , and robotics . Recent work includes diffusion-based reinforcement learning , hindsight experience prioritization , and hybrid manipulation planning , often addressing challenges in sequential task execution and tactile-based control. Key trends in his publications revolve around robotic manipulation , motion planning , and human-robot interaction . He has contributed to conferences like NeurIPS , ICRA , IROS , and journals such as IEEE TRO and Scientific Reports .

• Artificial Intelligence
• Robotics
• Deep Learning
• +5 more

Professor Cem Evrendilek is a faculty member in the Department of Computer Engineering at Izmir University of Economics, Turkey, holding the rank of Professor with current active status. His institutional email is cem.evrendilek@ieu.edu.tr. His research spans algorithmic complexity and geometric computation, with primary focus areas including: Computational Geometry (specializing in orthogonal polygon covering problems) Wireless Sensor Network Localization (energy-efficient methods and trilateration) NP-hard Problem Analysis (proving complexity for geometric and network problems) Approximation Algorithms for combinatorial optimization Analysis of his 2008-2018 publications reveals consistent work on geometric covering problems and sensor network localization. Key trends include proving NP-completeness for orthogonal polygon covering variants, developing energy-efficient mobile beacon localization techniques, and analyzing trilateration with noisy measurements. His work frequently intersects computational geometry with practical wireless network applications, demonstrating strong theoretical foundations applied to real-world constraints. Collaborative patterns show frequent co-authorship with Hüseyin Akcan (on localization algorithms), Burkay Genç, and Brahim Hnich (on computational geometry problems).

• Algorithms
• Computational Geometry
• Wireless Sensor Networks
• +1 more

Hüseyin DEMİRCİ is an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Information Systems Engineering. He holds a doctorate in Computer and Information Engineering from Sakarya University, where his thesis focused on designing a novel metaheuristic algorithm inspired by electricity movement in resistive media. Education: PhD (2015), MSc (2014), and BSc (2012) in Computer-related fields His research spans artificial intelligence, optimization algorithms, and decision-making systems, with a particular emphasis on metaheuristic methods like particle swarm optimization and genetic algorithms. He has applied these techniques to problems in surface reconstruction and real-time systems. Hüseyin also contributes to education through his role as a Research Assistant and has explored interdisciplinary domains such as feature selection, data clustering, and sustainable development-aligned computational approaches.

• Artificial Intelligence
• Machine Learning
• Metaheuristic Algorithms
• +9 more

Hüsnü Dal is a Professor at Middle East Technical University (METU) in Ankara, Turkey, specializing in computational mechanics of materials. His research bridges engineering and biomedical applications through advanced computational modeling techniques. Education: Bachelor's Degree, Middle East Technical University, 2001 Master's Degree, University of Stuttgart, 2005 PhD, Dresden University of Technology, 2011 Research Focus: Prof. Dal's work centers on computational micromechanics, multiscale and multifield problems, and materials theory. He investigates fracture in multiphysics media with applications in lithium-ion batteries and tissue mechanics, developing novel constitutive models for complex material behaviors under extreme conditions. His research integrates thermomechanical coupling, viscoplasticity, and data-driven approaches to solve engineering challenges in both synthetic polymers and biological systems. Publication Trends: Recent publications (2023-2025) reveal a dominant focus on data-driven constitutive modeling and phase-field fracture methods. His work spans rubber mechanics, polymeric foams, biological tissues, and battery materials, characterized by strong interdisciplinary connections between materials science, biomechanics, and computational engineering. Key themes include anisotropic hyperelasticity, thermo-viscoplastic fracture, and spatial property variations in additively manufactured materials.

• Computational micromechanics
• Multiscale and multifield problems
• Materials theory
• +3 more

Alp Bassa is a Professor of Mathematics at Boğaziçi University, affiliated with the Department of Mathematics. He holds a Ph.D. in Mathematics from Universität Duisburg-Essen (2007) and dual bachelor's degrees in Computer Engineering and Mathematics from Middle East Technical University (2004). His research focuses on Number Theory, Algebraic Geometry, and their applications in Cryptography and Finite Fields. Education: Ph.D. in Mathematics, Universität Duisburg-Essen, 2007 Bachelor of Science in Computer Engineering & Mathematics, Middle East Technical University, 2004 Research Interests: Professor Bassa investigates algebraic structures over finite fields, including Drinfeld modules, function fields, and their cryptographic applications. His work bridges Number Theory and Geometry, with contributions to coding theory and the construction of algebraic curves with optimal properties. Recent Projects: TÜBİTAK 2509: Curves over Finite Fields, Jacobian Varieties, and Abelian Varieties (2018–2020) BAP-10540: Curves over Finite Fields and Irreducible Polynomials (2015–2017) Teaching: Recent courses include foundational mathematics (Math 101, Math 102), advanced topics (Math 344, Math 525), and specialized courses in cryptography and algebraic geometry.

• Number Theory
• Algebraic Geometry
• Cryptography
• +3 more

Caner Özer is a Researcher affiliated with Istanbul Technical University's Department of Artificial Intelligence and Data Engineering and the University of Twente's MIA group. He holds a PhD in Computer Engineering from Istanbul Technical University (2020), an MSc in Telecommunication Engineering (2017-2020), and a BSc in Electronics and Communications Engineering (2013-2017). His research focuses on medical imaging AI, explainable artificial intelligence (XAI), deep learning applications in healthcare, and computer vision techniques for artifact detection in medical imaging. He has conducted visiting research at the University of Twente (2024) and serves on academic committees at Istanbul Technical University. Research interests include developing explainable models for mammogram analysis, enhancing medical image quality assessment via transformers and neural networks, and addressing challenges in cardiovascular MRI segmentation through motion artifact detection. His work bridges deep learning theory with practical clinical applications, emphasizing transparency and accuracy in AI-driven medical diagnostics. Notable contributions include cross-domain artifact correction for cardiac MRI, joint CNN-RNN models for intracranial hemorrhage detection, and XAI methods for chest X-ray analysis. His research has been published in top-tier venues with a focus on medical imaging and deep learning advancements.

• Artificial Intelligence
• Medical Imaging
• Deep Learning
• +3 more