جست‌وجوی استاد و پژوهشگر

Osman Kaan Erolمشاهده پروفایل

دانشیار

• Optimization Algorithms
• Heuristic and Metaheuristic Methods
• Control Systems
• +۳ مورد دیگر

Assoc. Prof. Dr. Osman Kaan Erol is affiliated with Istanbul Technical University , where he serves in the Department of Control and Automation Engineering . His primary research focuses on optimization algorithms and their applications in engineering systems. Doctorate in Control and Computer Engineering Teaching and research at Istanbul Technical University since 2003 Industry experience at BEKO Electronics (2000-2003) and ABC CEDETAŞ (1995-2000) Research Interests include: Big Bang-Big Crunch optimization algorithm Differential Evolution methods Heuristic and metaheuristic approaches Applications in structural engineering, control systems, and transportation Search space reduction techniques Hybrid algorithm design Publication Trends show a consistent focus on optimization algorithms ( Big Bang-Big Crunch , Differential Evolution ), with applications spanning airport operations , structural design , and preventive control . His work emphasizes algorithm hybridization and convergence improvements. Project Leadership includes: Industrial data collection systems AI-assisted service systems for concrete plants Hydrophore control systems under ERP regulations Electrically heated underwear design

Ayhan Günمشاهده پروفایل

دانشیار

• Control Systems
• Mathematical Modeling in Electrical Engineering
• Artificial Neural Networks
• +۱۲ مورد دیگر

Assoc. Prof. Dr. Ayhan Gün is an Associate Professor in the Department of Electrical and Electronics Engineering at Kütahya Dumlupınar University's Faculty of Engineering. With a career spanning over two decades, he has held various academic positions including Research Assistant, Assistant Professor, and currently Associate Professor since 2024. His extensive administrative experience includes serving as Head of the Control and Command Systems Department (2007-2021) and various leadership roles in university-industry collaboration initiatives. Dr. Gün completed his Bachelor's degree at Near East University (1991-1996), Master's at Dumlupınar University (1998-2001), and PhD at Eskişehir Osmangazi University (2001-2007). His research focuses on control systems, mathematical modeling, artificial neural networks, robotics, SCADA, PLC programming, electromechanical systems, nonlinear control, fuzzy logic, optimization techniques, automation, biomechanics, and mechatronics. His recent publications demonstrate a consistent research trajectory in control engineering, with particular emphasis on optimization algorithms applied to quadrotor control, inverted pendulum systems, and electrical motor design. His work bridges theoretical control concepts with practical implementations in robotics and power systems. A significant portion of his research involves applying swarm intelligence and evolutionary algorithms to solve complex control problems. Bilim, Sanayi ve Teknoloji Bakanlığı Kurumsal Kapasitenin Arttırılması (2016) BİLİM SANAYİ VE TEKNOLOJİ BAKANLIĞI Çift Beslemeli İndüksiyon Generatörü Tasarımı ve İmalatı (2016) Dr. Gün has supervised multiple graduate students and managed numerous research projects, including the current 'Robotic Arm Design and Implementation for Patients with Hemiparetic Arms' project. His external roles include serving as an expert witness for judicial institutions, project referee for TÜBİTAK, and publication reviewer for IEEE Transactions. He has also contributed to regional development through his work with Kütahya Governorship's Planning and Development Board.

Hüseyin DEMİRCİمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Metaheuristic Algorithms
• +۹ مورد دیگر

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.

• Nuclear Reactor Engineering
• Computational Fluid Dynamics
• Thermal Hydraulics
• +۴ مورد دیگر

Prof. Uner Colak is a Professor at Istanbul Technical University's Energy Institute, specializing in nuclear reactor engineering, computational fluid dynamics, and thermal hydraulics. His research focuses on high-temperature reactors, neutron flux analysis, and reactor safety. He has led numerous projects on nuclear fuel management, hydrogen production, and energy systems optimization. Colak has received the TÜBA Scientific Copyright and Translated Works Awards Program (TEÇEP) in 2015. His work spans reactor core design, neutron transport analysis, and droplet dynamics, with over 49 publications and 12 projects since 2001. Research interests include nuclear reactor core physics, computational modeling for reactor safety, and advanced energy systems. His recent work involves validating reactor analysis codes, optimizing load dispatch algorithms, and investigating droplet-surface interactions for heat transfer applications. Projects include developing pebble flow dynamics for high-temperature reactors and assessing nuclear power localization strategies. His articles highlight contributions to reactor physics, fluid dynamics, and energy policy. Current activities include active projects on hydrogen technologies and sustainable energy solutions until 2027. Colak collaborates internationally, contributing to global nuclear energy advancements and training future researchers through ongoing theses supervision.

• Power Systems
• Smart Grids
• Transient Stability
• +۷ مورد دیگر

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.

BÜLENT HAZNEDARمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Fuzzy Logic
• +۵ مورد دیگر

Bülent Haznedar is an Associate Professor in the Department of Computer Engineering at Gaziantep University's Faculty of Engineering, a position he has held since 2024. Previously, he served as Doctor Lecturer at Gaziantep University (2021-2024) and held academic positions at Hasan Kalyoncu University (2013-2021) and Erciyes University (2011-2013), where he progressed from Lecturer to Department Head. His educational qualifications include: Doctorate in Computer Engineering from Erciyes University (2011-2017) Master's degree in Computer Engineering from Erciyes University (2007-2010, with thesis) Licence degree in Computer Engineering from Erciyes University (2003-2007) Dr. Haznedar's research centers on Artificial Intelligence and Machine Learning applications, with significant contributions in hydrological modeling (streamflow forecasting using hybrid ANFIS algorithms), renewable energy (solar radiation optimization), medical diagnostics (thyroid nodule classification and cancer detection), and cultural heritage informatics (3D point cloud segmentation for historical buildings). His work consistently integrates fuzzy logic systems with metaheuristic optimization techniques to solve complex prediction problems. Analysis of his 29 journal articles (2016-2024) reveals a dominant focus on Adaptive Neuro-Fuzzy Inference Systems enhanced by evolutionary algorithms (PSO, GA, ABC) across hydrology and medical domains, with recent expansion into sustainable energy and heritage preservation. His publications show increasing interdisciplinary collaboration, particularly in TUBITAK-funded projects. His scientific recognition includes: TUBITAK Publication Encouragement Awards (2018, 2023) TUBITAK PhD Scholarship (2011) TUBITAK Master's Scholarship (2008) Dr. Haznedar has supervised eight master's theses on AI applications in streamflow forecasting, energy prediction, cancer classification, and heritage modeling. His research is supported by seven projects, most notably the TUBITAK 1001 project (2019-2023) developing Heritage Building Information Modeling for Turkey's cultural heritage restoration. He also contributed to TUBITAK's Digital Prosthesis Workshop initiative. While specific laboratory affiliations aren't detailed, his leadership in the TUBITAK cultural heritage project indicates active collaboration with multidisciplinary teams spanning engineering, computer science, and heritage conservation disciplines.

• Renewable Energy Systems
• Photovoltaic Power Plants
• Energy Optimization
• +۳ مورد دیگر

Ali DURUSU is a researcher at Yıldız Technical University, College of Engineering , with a focus on Renewable Energy Systems and Photovoltaic Power Plants . His work spans techno-economic modeling, energy optimization, and smart grid integration. Research Interests : Solar power plant design, grid integration, energy economics, MPPT algorithms, hybrid systems, and smart grid technologies Advisory : Has advised 25 theses on renewable energy topics Projects : Involved in 15 research initiatives Recent publications emphasize peer-to-peer energy trading, distributed storage, and optimization techniques. He has contributed to 80 WoS-indexed publications with significant citations (H-Index: 8 in WoS, 11 in Scopus) and participated in 43 peer-reviewed conferences.

• Electrical Machines and Energy Conversion
• Control Theory and Applications
• Artificial Intelligence
• +۳ مورد دیگر

Hilmi AYGÜN is an Assistant Professor in the Department of Mechatronics Engineering at Karabük University's Faculty of Engineering and Natural Sciences, where he has been serving since 2019. His academic career began as a Research Assistant in the Electrical and Electronics Engineering Department from 2009-2019 before transitioning to his current position in Mechatronics Engineering. He also serves as the Erasmus Coordinator for both the Mechatronics Engineering Department and the university since 2021. Education: PhD in Electrical and Electronics Engineering (2011-2019), Karabük University, Institute of Science MSc in Electrical and Electronics Engineering (2010-2011), Karabük University, Institute of Science BSc in Electrical and Electronics Engineering (2003-2007), Kırıkkale University, Faculty of Engineering Hilmi AYGÜN's research primarily focuses on electrical machines and energy conversion systems, with particular emphasis on motor control algorithms for electric vehicle applications. His work integrates control theory with artificial intelligence techniques, especially optimization algorithms like Particle Swarm Optimization (PSO) and the Yusufcuk Algorithm. He has made significant contributions to field-oriented control of induction motors, DC motor control systems, and wind energy applications. His publication record shows a clear trajectory toward increasingly sophisticated control systems for electromechanical applications, with recent work focusing on metaheuristic methods for motor control, optimization of wind energy systems, and advanced DC motor control techniques. His research bridges theoretical control concepts with practical engineering applications, particularly in transportation and renewable energy sectors. Hilmi AYGÜN has successfully advised at least one Master's student, Hersh Hasan Taha Al Dawoodı, whose thesis focused on field-oriented control of induction motors using metaheuristic methods. He has participated in two major research projects: one on optimal flux reference direct torque control for asynchronous motors used in electric vehicles (2015-2019), and another on controlling bed temperature in fluidized bed boilers using PSO-PID controllers (2011-2013). As an educator, he has taught numerous courses including Electric Machine Dynamics, Modeling and Control of Biomedical Systems, Control of Electric Machines, Electric and Hybrid Vehicles, Industrial Automation, and various electronics courses. His teaching spans both undergraduate and graduate levels, demonstrating his versatility across multiple engineering disciplines within the mechatronics field.

• Nuclear Engineering
• Computational Fluid Dynamics
• Renewable Energy Systems
• +۳ مورد دیگر

Professor Üner Çolak is affiliated with the Energy Institute at Istanbul Technical University, focusing on nuclear engineering, computational fluid dynamics, and renewable energy systems. His work spans reactor simulation, droplet dynamics, and energy optimization algorithms. Nuclear Reactor Engineering Computational Fluid Dynamics Renewable Energy Systems High-Temperature Reactors Droplet Dynamics Energy Optimization Algorithms Recent research includes validating AGREE HTR code with PROTEUS experiments (2025), developing pelican optimization algorithms for load dispatch (2024), and numerical studies on droplet interactions (2023). His projects address pebble-bed reactor dynamics, hydrogen technologies, and export-oriented localization strategies for nuclear plants. Scientific recognition includes the TÜBA TEÇEP Award (2015). Current projects involve pebble flow dynamics hydrogen production low-quality heat source utilization TRIGA reactor diffuser optimization

Baran Toprakمشاهده پروفایل

استادیار

• Geotechnical Engineering
• Foundation Engineering
• Soil Mechanics
• +۲ مورد دیگر

Baran Toprak serves as an Assistant Professor in the Geotechnics Department within the Department of Civil Engineering at Kırıkkale University's Faculty of Engineering and Natural Sciences. Appointed to this faculty position in February 2020 following completion of his doctorate, he has been affiliated with the university since 2002 after military service completion in 2001. His academic credentials include: Civil Engineering degree from Balıkesir University Faculty of Engineering and Architecture (1999) Master's in Geotechnics (2005) Doctorate (2019) Dr. Toprak's research centers on Geotechnical Engineering with specialized expertise in foundation design under dynamic loads, soil-structure interaction, and innovative soil improvement techniques. His work addresses critical challenges in low-bearing-capacity soils through methods like fly ash column treatment and advanced in-situ testing (CPT/SPT). He investigates seismic behavior of reinforced concrete structures on improved soils and develops protective systems like gabion walls for blast mitigation, bridging theoretical analysis with practical field applications across earthquake-prone regions of Turkey. Analysis of his 15 publications (2013-2025) reveals consistent focus on geotechnical investigation methodologies, foundation engineering in challenging soils, and dynamic soil-structure interaction. Key trends include utilization of industrial byproducts (fly ash, slag) for soil stabilization, optimization of structural systems via metaheuristic algorithms, and detailed post-earthquake damage assessments linking soil amplification to building resonance. His research demonstrates strong field application emphasis through municipal projects in Kırıkkale and Düzce provinces. No scientific awards were documented in the source materials. No information regarding student advising, research grants, or laboratory leadership was provided in the available documentation.

• Electrical Energy and Power Systems
• Power System Optimization
• Renewable Energy Integration
• +۴ مورد دیگر

Salih ERMİŞ serves as Assistant Professor and Department Head in the Department of Electrical and Electronics Engineering at Kırşehir Ahi Evran University's Faculty of Engineering and Architecture. With 25+ years of continuous service since 2000, he progressed from Instructor to Doctoral Lecturer in 2018 and assumed departmental leadership in 2022. His academic foundation includes a PhD (2019), MSc (2003), and BSc (2000) in Electrical Education from Gazi University, complemented by English proficiency certification (YDS 55, 2015). His educational journey demonstrates deep institutional commitment: PhD: Electrical Education, Gazi University Institute of Science (2004-2019) MSc: Electrical Education (Thesis), Gazi University Institute of Science (2001-2003) BSc: Electrical Education, Gazi University Faculty of Technical Education (1995-2000) ERMİŞ's research centers on electrical energy systems with emphasis on metaheuristic optimization applications. His work bridges theoretical algorithms and practical power grid challenges, particularly in voltage stability, renewable integration, and smart grid technologies. Recent publications reveal a strategic shift toward photovoltaic forecasting and educational technology, including augmented reality tools for circuit analysis. His methodology consistently applies nature-inspired algorithms (Ant Colony, Grey Wolf, Particle Swarm) to solve multi-objective power flow problems while addressing agricultural energy needs and distribution network efficiency. His publication portfolio shows consistent growth in high-impact domains, with 2023-2025 works focusing on distributed generation optimization, PMU placement, and environmental economic dispatch. The research demonstrates strong industry relevance through industrial control circuit analysis and solar radiation-based output estimation. Award recognition includes: Best Paper Award at 2017 IEEE ICRERA for FACTS devices research As an advisor, he has supervised two Master's theses on photovoltaic forecasting and metaheuristic load flow analysis. His grant leadership spans seven projects including mobile AR applications for engineering education (2025-2027), short-circuit fault analysis software (2023-2024), and solar panel efficiency testing (2021-2023). Collaborative work with researchers like Ramazan Bayındır and Mehmet Yeşilbudak over 2016-2023 demonstrates sustained interdisciplinary teamwork. Current initiatives focus on visual programming tools for power system education and hybrid PV/wind optimization.

• Statistical Analysis and Applications
• Machine Learning
• Data Mining
• +۴ مورد دیگر

Dr. Uğur ERCAN is currently serving as an Associate Professor at Akdeniz University's Department of Informatics. He holds a PhD in Econometrics from Akdeniz University (2016) and a master's degree in Mathematics (2008), with a bachelor's degree in Computer Engineering from Mersin University (2003). PhD in Econometrics (Akdeniz University, 2016) MSc in Mathematics (Akdeniz University, 2008) BSc in Computer Engineering (Mersin University, 2003) His research focuses on statistical analysis, machine learning, data mining, and optimization, with notable applications in agriculture, public health, and consumer behavior. Recent work includes machine learning models for predicting crop quality, alcohol consumption patterns, and energy systems optimization. Scientific output trends show interdisciplinary applications of machine learning across agricultural engineering, health economics, and renewable energy. Publications include predictive models for fruit characteristics, econometric analyses of household expenditures, and optimization algorithms for solar energy systems. He has contributed to 51 publications (Scopus) and maintains active research in quantitative methods, with expertise in neural networks, regression analysis, and ensemble learning techniques. His work aligns with UN Sustainable Development Goals for responsible consumption and production.

Yüksel Yurtayمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Data Science
• +۸ مورد دیگر

Assoc. Prof. Dr. Yüksel Yurtay is an active faculty member at Sakarya University's Faculty of Computer and Information Sciences, Department of Data Science and Analytics. With a career spanning over three decades at the university since 1993, he has established himself as a prominent researcher and educator in the fields of data science, artificial intelligence, and business analytics. Education: Doctorate (2011-2020): Sakarya University, Institute of Business Administration/Production Management and Marketing, Thesis: "An empirical study on the impact of the dashboard on decision processes in the context of supply chain management" Master's (1996-1998): Sakarya University, Institute of Social Sciences/Production Management and Marketing, Thesis: "Activity based costing system and an application in electro-mechanical industry" Bachelor's (1987-1991): Anadolu University, Faculty of Arts and Sciences/Mathematics Dr. Yurtay's research focuses on the intersection of data science and business applications, with particular emphasis on dashboard systems, key performance indicators, and supply chain management. His work bridges theoretical computer science with practical business applications, developing innovative solutions for performance monitoring, decision support, and process optimization. His research portfolio demonstrates consistent productivity with publications spanning from 2018 through 2025, showing no signs of slowing down. Analysis of Dr. Yurtay's recent publications (2018-2025) reveals several key research trajectories: a strong focus on dashboard and KPI systems for business decision-making, growing interest in AI applications for emotion recognition (particularly in call center contexts), development of novel metaheuristic algorithms for optimization problems, and application of computer vision techniques for specialized detection tasks. His work consistently combines theoretical algorithm development with practical business applications. Dr. Yurtay has successfully secured research funding from prestigious sources including TÜBİTAK (project 1505) and industry partnerships with companies like Turkcell Global Bilgi. His current projects focus on real-time emotion recognition using deep learning and business process optimization. As an educator, Dr. Yurtay teaches core courses in numerical analysis, software engineering, computer engineering design, and data science. He has supervised graduate theses, including Akın YAŞAR's work on real estate photo quality evaluation using deep learning. His teaching portfolio reflects his expertise across both theoretical computer science and applied data analytics.

Erdal Erelمشاهده پروفایل

استاد

• Production Operations Management
• Manufacturing Systems Design
• Assembly and Disassembly Line Balancing
• +۴ مورد دیگر

Erdal Erel is a Professor of Operations Management (OM) and currently serves as the Vice Rector in charge of administrative and financial affairs at Bilkent University's Faculty of Business Administration. He holds a B.S. in Industrial Engineering from Istanbul Technical University (1981), an M.S. from Stanford University (1983), and a Ph.D. from Virginia Polytechnic Institute and State University (1987). His academic career has been dedicated to advancing research in Production Operations Management, focusing on manufacturing systems design, assembly/disassembly line balancing, scheduling, and project management. Erel's educational background includes: B.S. in Industrial Engineering, Istanbul Technical University (1981) M.S. in Industrial Engineering, Stanford University (1983) Ph.D. in Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University (1987) His research interests span several critical areas of operations management, including manufacturing systems design, assembly and disassembly line balancing, scheduling and sequencing methodologies, and project management. He has made significant contributions to robust optimization techniques applied to time-cost trade-offs and stochastic modeling in production systems. His work emphasizes practical solutions for complex operational challenges through advanced algorithms like ant colony optimization and beam search methods. Erel's publications reflect a focus on optimization in production systems, scheduling algorithms, and decision models under uncertainty. His research bridges theoretical advancements with real-world applications in manufacturing and service industries, addressing issues such as cost minimization, robust scheduling, and efficiency improvements in assembly line operations. Erel has contributed extensively to his field but no specific scientific awards are mentioned in the provided text. No specific information about advising students or grants is provided in the text. Erel's involvement in collaborative projects, including work with colleagues like I. Sabuncuoglu and J.B. Ghosh, highlights his role in interdisciplinary research teams focused on operational efficiency and advanced manufacturing technologies.

• Supply Chain Management
• Logistics
• Artificial Intelligence
• +۳ مورد دیگر

Batin Latif AYLAK serves as Associate Professor in the Department of Industrial Engineering at the Faculty of Engineering, Turkish-German University, Turkey. Previously, he held an Assistant Professor position at Hitit University starting in 2015. His academic career spans over a decade of research at the intersection of industrial engineering, logistics, and artificial intelligence. His educational foundation includes: Doctorate in Mechanical Engineering from University of Duisburg-Essen (2010-2015) Master's degree in Mechanical Engineering from University of Duisburg-Essen (2008-2010) Bachelor's degree in Industrial Engineering from Istanbul Kültür University (2001-2006) with full scholarship Dr. AYLAK's research pioneers the integration of artificial intelligence in supply chain optimization, with particular emphasis on sustainable logistics systems. His work bridges theoretical advancements with practical applications in blockchain implementation for supply chain transparency, machine learning-driven energy forecasting, and intelligent warehouse management. He has developed novel frameworks like SustAI-SCM for agentic AI in sustainable supply chains and contributed significantly to understanding digital transformation in Turkey's logistics sector. His publication trajectory (2021-2025) reveals a strategic evolution from foundational logistics research toward cutting-edge AI applications. Early work focused on optimization algorithms and blockchain integration, while recent publications demonstrate leadership in agentic AI systems for sustainability, advanced predictive modeling for renewable energy, and pandemic-responsive supply chain solutions. This progression highlights his adaptation to emerging technological paradigms while maintaining core focus on supply chain resilience. No scientific awards or fellowships were documented in the provided materials. Dr. AYLAK has secured competitive research funding including project BAP TAÜ - 2018BM0028 for digital trend analysis in Turkey's logistics sector. While his publications indicate collaborative research with multiple co-authors across institutions, no formal graduate student advisement relationships were specified in the available documentation.