Selim Şeker is a part-time Professor at Bogazici University. His research focuses on electromagnetic wave propagation, electromagnetic compatibility (EMC), biomedical effects of radiation, and remote sensing. He has contributed to interdisciplinary studies spanning neurology, telecommunications, and environmental science. Research interests include advanced MRI techniques for glial tumors, neuroimaging for hydrocephalus diagnostics, and modeling electromagnetic radiation effects in biological systems. His work bridges theoretical electromagnetics with practical applications in healthcare and telecommunications infrastructure. Key publications span neuroimaging case studies, tumor recurrence analysis, and propagation models for wireless systems. Notable contributions include curve-fitting models for energy consumption forecasting and analysis of rare medical cases involving cranial trauma and metastatic carcinomas.
Murat SARDUVAN is an Associate Professor in the Department of Mathematics at Sakarya University . His research focuses on matrix theory, linear and multilinear algebra, numerical analysis, and applied mathematics, with particular interest in special matrix types (tripotent, idempotent, involutive) and their linear combinations. Research spans matrix equations, spectral theory, nonsingularity conditions, and nearness problems Published in journals like Journal of Numerical Mathematics , Linear & Multilinear Algebra , and Acta Universitatis Apulensis Supervised 6 graduate theses on matrix combinations and partial orders Awarded Teşekkür Belgesi and Takdir Belgesi for academic contributions
Işın Erer is a Professor at the Department of Electronics and Communication Engineering, Faculty of Electrical and Electronic Engineering, Istanbul Technical University (ITU). She is actively involved in research on radar signal processing, artificial intelligence, and image analysis, with a focus on ground-penetrating radar (GPR) and remote sensing applications. University: Istanbul Technical University School: Faculty of Electrical and Electronic Engineering Department: Department of Electronics and Communication Engineering Academic Rank: Professor Email: ierer@itu.edu.tr Her research interests span signal processing, radar systems, clutter removal, target detection, deep learning, vision transformers, U-Nets, and vital signs detection using stepped-frequency radar . She applies advanced machine learning techniques to enhance radar imaging and improve performance in challenging environments such as debris fields and outdoor conditions. The recent publication trends indicate a strong focus on integrating deep learning models (e.g., Vision Transformers, YOLOv5, U-Net) with radar signal processing for clutter removal, image restoration, and segmentation . Her work combines low-rank approximations, autoencoders, B-spline activation functions, and attention mechanisms to improve accuracy and robustness in GPR and remote sensing imagery. Applications include parcel boundary delineation, road segmentation, and life detection in search-and-rescue scenarios. She has received notable recognition for her academic mentorship: Best PhD Thesis Advisor in Telecommunications Engineering Program, 2018 She leads multiple active research projects funded by TÜBİTAK and ITU-BAP, focusing on real-time AI-based radar systems, through-wall vital sign detection, and clutter removal in GPR. She has supervised numerous graduate students, with 47 theses in progress or completed. Her research group works on both theoretical algorithm development and practical system implementation, bridging the gap between academia and real-world deployment. Current projects include developing integrated AI models for real-time GPR systems and ultra-wideband radar methods for behind-obstacle detection.
Mithat Can Özin serves as a Researcher in the Department of Mechanical Engineering at Istanbul Technical University (ITU), specializing in precision sensor design and biomechanical systems. His work bridges theoretical modeling with experimental validation across multiple engineering domains. Research Focus: Dr. Özin's primary investigations center on multi-axis force/moment sensors , particularly cross-beam configurations requiring advanced optimization techniques. His expertise spans Structural optimization of compliant mechanisms Friction dynamics in surgical robotics Stress topology analysis for sensor calibration Genetic algorithm applications in sensor design His recent publications demonstrate consistent advancement in Gaussian process modeling and Pareto optimality approaches for force sensor development. Awards & Recognition: While specific awards aren't documented, his work shows significant impact with 18 Scopus h-index 20 Mendeley readers across publications 2 patents referencing his research Multiple publications in IEEE Sensors Journal and Mechanics Based Design Collaborative Networks: Özin maintains active research partnerships within ITU's mechanical engineering faculty, particularly with Professors Sümer and Koç. His work intersects with robotics, biomechanics, and microscale material science, evidenced by publications spanning surgical tools to PDMS-glass interfaces. Current projects focus on next-generation force sensors with applications in minimally invasive surgery and industrial robotics.
Prof. Fatma İnci Albayrak is a Professor at the Department of Mathematics Engineering within the Faculty of Chemical and Metallurgical Engineering at Yildiz Technical University . She holds a doctorate, postgraduate, and undergraduate degree in Mathematics Engineering from the same institution. Her research spans Mathematics , Optimization , Natural Sciences , and Fuzzy Modeling , with a focus on applying fuzzy logic to complex engineering and operational problems. Education: Doctorate (1993–1997), Yildiz Technical University Postgraduate (1990–1993), Yildiz Technical University Undergraduate (1986–1990), Yildiz Technical University Her publications reflect expertise in fuzzy systems , multi-objective optimization , differential equations , and nanostructured materials . She has contributed to journals like Physica Scripta , Canadian Journal of Chemical Engineering , and Cellulose , often addressing challenges in biomedical applications, transportation networks, and nanotechnology. She has served as a peer reviewer for Soft Computing and Promet journals. She is affiliated with the Multidisciplinary Nanoscience Technology working group at Yildiz Technical University since 2021, integrating nanomaterials with mathematical modeling. Her work bridges theoretical mathematics and practical engineering, demonstrated through collaborations in polymer nanocomposites, heat exchanger optimization, and traffic assignment problems.
Dr. Fahrettin Horasan is an Associate Professor in the Department of Computer Engineering at the Faculty of Engineering and Natural Sciences . His research focuses on applied computational methods in data security, machine learning, and information retrieval systems. Specialized in medical image watermarking and encryption using matrix decomposition techniques (SVD, ULV) Developed novel collaborative filtering recommender systems with hybrid approaches and matrix approximation Contributions in sentiment analysis for healthcare and e-commerce domains His recent publications highlight interdisciplinary work combining cryptology, biomedical imaging, and large-scale data processing. Notable methods include chaotic system-based encryption, latent semantic indexing, and gradient boosting for darknet traffic analysis. While specific awards, educational background, and student advisement details are not publicly detailed in the provided texts, his technical output reflects active engagement in computational science advancements.
Demet Ersoy Özdek is an Assistant Professor in the Department of Mathematics at Izmir University of Economics since 2021. Previously, she worked as a part-time lecturer at the same institution from 2014 to 2021 and as a research assistant from 2006 to 2014. She completed her PhD in Mathematics at Dokuz Eylül University in 2014 under the supervision of Prof. Dr. Valery G. Yakhno. Education: BSc in Mathematics (2005), Dokuz Eylül University MSc and PhD in Mathematics, Dokuz Eylül University Research Interests span computational mathematics, differential equations, and mathematical modeling. Her work focuses on wavelet methods (Legendre, Laguerre, Gegenbauer), Green's functions for layered structures, and numerical solutions for nonlinear systems. Collaborations include Sevin Gumgum and Necdet Bildik. Key Article Trends include the application of wavelet methods to delay differential equations, Green's function formulations for vibration analysis, and polynomial-based numerical solutions for epidemiological and astrophysical models. Her publications (2013–2024) reflect interdisciplinary applications of mathematical physics to engineering and biological systems. Contact: Email: demet.ersoy@ieu.edu.tr ORCID: 0000-0003-3877-6739
Dr. İsmail AKTÜRK serves as an Assistant Professor in the Computer Science Department within Ozyegin University's Faculty of Engineering. Previously, he held an Assistant Professor position at the University of Missouri - Columbia's Department of Electrical Engineering and Computer Science for four years. His academic foundation includes a Ph.D. in Electrical and Computer Engineering from the University of Minnesota, Twin Cities. Education: Ph.D. in Electrical and Computer Engineering, University of Minnesota, Twin Cities, 2017 M.S. in Computer Engineering, Bilkent University, 2013 M.S. in Electrical Engineering, Louisiana State University, 2009 B.S. in Computer Engineering, Doğuş University, 2007 Dr. AKTÜRK's research centers on Computer Architecture with specialized expertise in brain-inspired computing and neuromorphic systems . He pioneers unconventional computing paradigms that integrate memory and processing units to eliminate energy-intensive data transfers inherent in traditional von Neumann architectures. His work employs hardware/software co-design methodologies to enhance energy efficiency for data-intensive applications like deep learning through spatial and temporal approximations. He directs the Computer Architecture and System Technologies Lab, where his research group develops application-specific systems exploiting novel devices and algorithmic advancements. Dr. AKTÜRK actively mentors graduate students in creating energy-efficient computing solutions for emerging computational challenges.
Can Deha Karıksız is an Assistant Professor of Mathematics at Özyeğin University's Faculty of Engineering. He holds a PhD in Mathematics from Sabancı University (2014), with prior degrees from Sabancı University (2007, MSc) and Middle East Technical University (2005, BSc). His academic journey includes a postdoctoral fellowship at Adam Mickiewicz University (2014-2015) supported by a TÜBİTAK grant and an instructorship at the University of Zurich (2019-2020). Assistant Professor, Özyeğin University (current) Postdoctoral Researcher, Adam Mickiewicz University Instructor, University of Zurich His research spans three primary domains: Applications of functional analysis to complex analysis Dynamics of linear operators Mean-field games and stochastic control Combining mathematical rigor with computational approaches, his work bridges theoretical analysis with practical implementation in multi-agent systems and reinforcement learning frameworks. Recent publications focus on mean-field games (2019-2024), particularly through algorithmic approaches like Q-learning, value iteration, and inverse reinforcement learning. Earlier work (2018) examines linear operator dynamics on real analytic function spaces. Key trends show increasing specialization in stochastic control and game theory applications to machine learning and engineering. Scientific achievements include: TÜBİTAK Postdoctoral Research Fellowship He has taught diverse courses across institutions and levels since 2005, including Linear Algebra, Calculus sequences for engineering/social sciences, Differential Equations, and graduate-level Numerical Linear Algebra and Analysis II. His teaching portfolio demonstrates expertise in both foundational mathematics and advanced computational methods.
Erhun Kundakcıoğlu is a Professor in the Department of Industrial Engineering at Ozyegin University's Faculty of Engineering. He received his Ph.D. in Industrial and Systems Engineering from the University of Florida (2009) with a minor in Computer and Information Science and Engineering, following an M.S. in Industrial Engineering at Sabancı University (2004) and B.S. at Bilkent University (2002). He served as Assistant Professor at University of Houston (2009-2013) and Director/Distinguished Scientist at Optym (2019-2021). Ph.D.: Industrial and Systems Engineering, University of Florida (2009) M.S.: Industrial Engineering, Sabancı University (2004) B.S.: Industrial Engineering, Bilkent University (2002) His research focuses on combinatorial optimization and decision making under uncertainty , with applications in healthcare analytics , sustainable energy systems , supply chain management , and data science . He has developed optimization models for inventory control, lot sizing, and routing problems under uncertain demand/supply conditions, particularly in healthcare and humanitarian contexts. His work with the Datart Lab integrates mathematical programming into practical solutions for industry partners. Recent publications highlight his expertise in disaster relief inventory simulation, healthcare inventory management, and time series decomposition optimization. He supervises active graduate students including Deniz N. Yoltay (Ph.D.) and Buket İpek Akbal (M.S.). Early Career Award, TUBITAK Teaching Excellence Award, University of Houston Florida Chapter Scholarship, HIMSS Foundation As Associate Editor for the Journal of Global Optimization , Optimization Letters , and SN Operations Research Forum , he contributes to academic discourse in optimization and analytics. His consulting firm Datart R&D Management Consulting bridges academic research with industry applications in Turkey and abroad.
Professor Ali Olgun is affiliated with the Faculty of Engineering and Natural Sciences, Department of Mathematics, specializing in Applied Mathematics. His research focuses on fractional calculus, numerical analysis, and approximation theory. Academic Rank: Professor Department: Mathematics School: Engineering and Natural Sciences Research Interests His work bridges theoretical and applied mathematics, particularly in: Fractional differential equations Numerical methods for nonlinear PDEs Convergence properties of linear operators Mathematical modeling in ophthalmic surgery Publications Trend Recent publications emphasize conformable fractional derivatives, novel operator modifications, and clinical efficacy studies in glaucoma treatments. Collaborative Work Active in interdisciplinary research, particularly in mathematical modeling of ophthalmic procedures and approximation theory.
Serkan Özbay serves as an Associate Professor in the Department of Electrical and Electronics Engineering at Gaziantep University's Faculty of Engineering, Turkey. With academic appointments since 2003, he progressed from Lecturer to his current position (2024), maintaining continuous affiliation with the institution where he also completed all his degrees. His career demonstrates deep institutional integration and vertical advancement within the same department. His academic credentials were entirely earned at Gaziantep University: Doctorate (2007-2015): Institute of Science, Electrical and Electronic Engineering Master's (2003-2006): Institute of Science, Electrical and Electronics Engineering (Thesis) Licence (1997-2002): Faculty of Engineering, Electrical and Electronics Engineering Özbay's research centers on signal processing and machine learning applications, with significant contributions to computer vision for medical diagnostics (sinus segmentation, lung cancer detection) and security systems (image/video forgery analysis). His work bridges theoretical algorithms with practical implementations in edge computing and biomedical devices, evidenced by projects like real-time fall detection systems and metamaterial antennas. Recent publications show intensified focus on deep learning since 2020, particularly convolutional neural networks for medical imaging and object tracking. His publication trajectory reveals strategic interdisciplinary expansion: early work (2007-2015) concentrated on spectrum sensing and wireless communications, while post-2020 output pivoted toward AI-driven medical applications and digital forensics. Approximately 70% of his 22 publications (2019-2023) involve deep learning implementations, with strong institutional collaboration patterns—85% co-authored with Gaziantep University researchers. Journal publications predominantly appear in Q2-Q4 SCI-indexed engineering journals, while conference papers target international venues in computer vision and biomedical engineering. As an academic advisor, Özbay has supervised 16 graduate theses (1 PhD, 15 Master's) between 2017-2025, with 11 completed in 2020-2023 alone. Current advisees include students developing Raspberry Pi-based plate recognition systems and real-time fall detection solutions. He additionally mentors 15 undergraduate students in senior design projects annually, as evidenced by 2024 EEE498/499 project meetings. Administrative leadership includes Deputy Head of Department (2016), Erasmus Coordinator (2015-2016), and Institute Board membership (2020-2023).
Prof. Dr. İlker Tari is a distinguished academic in Mechanical Engineering, currently serving as a Professor at FMV Işık University , Istanbul, Turkey. Previously, he held a Professor position at Middle East Technical University (METU) from 1998-2022 and served as Visiting Professor at Technische Univ. München (2010-2012). His research focuses on Solar Energy Applications , Thermal Energy Storage , and Computational Heat Transfer . Education: PhD, Mechanical Engineering - Northeastern University (1998) SM, Nuclear Engineering - MIT (1994) MS, Nuclear Engineering - University of Michigan (1991-1994) BS, Nuclear Energy Engineering - Hacettepe University (1983-1987) Research Interests: His work specializes in: Solar Energy Systems for industrial applications and hybrid storage Thermal Management of electronics and fuel cells Radiative Transfer modeling in particulate media Fluidized Bed Technologies for energy storage Computational Fluid Dynamics (CFD) and DEM methods 3D Printing Applications in mechanical systems Scientific Contributions: Recent publications focus on: Advanced solar cooling systems Hybrid energy storage with phase change materials Mechanical properties of particle beds CFD-DEM integration for thermal modeling Optimization of industrial solar hybridization Renewable energy system analysis Student Supervision: Has supervised over 40 graduate theses including: Furkan Enes Yıldırım - 2025 Deniz Değirmenci - 2022 Ender ÖZDEN - 2015 Mehdi MEHRTASH - 2017 Özgür BAYER - 2009 Ömer EMRE ORHAN - 2007 Key Projects: EU H2020 INSHIP (2017-2020) TUBITAK 217M062 Solar Dryer (2017-2020) EU H2020 SFERA-III (2019-2023) EU H2020 SolarTwins (2020-2023) ECOSun Solar-ERANET (2020-2023) InnoSolPower CSP-ERANET (2021-2024) Professional Affiliations: President, International Center for Heat and Mass Transfer (2019) Member, Turkish Cogeneration Association (2021) Member, Turkish Thermal Science and Technology Association (2018) Member, American Society of Thermal and Fluids Engineers (2015)
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.
