جستجوی استاد راهنمای دانشگاهی

• Sustainable Architecture
• Energy Efficiency in Buildings
• Building Envelope Systems
• +۳ مورد دیگر

Dr. Dinçer Aydın is an Assistant Professor at the Department of Architecture , Trakya University 's Faculty of Architecture . With a career spanning from 2013, his work focuses on energy-efficient architecture , sustainable building systems , and project delivery methodologies . He serves on multiple commissions including the Construction and Environment Commission and Competition Commission since 2024, and contributes to KAPU/Thrace Architecture and Design Magazine as an editorial board member. His educational background includes a PhD in Architecture (2022) from Trakya University, where his dissertation proposed a sustainable project delivery system model for Türkiye. He holds a Master's in Architecture (2017) from the same institution, focusing on indoor environmental quality in high-rise residential buildings, and a Bachelor's in Architecture (2013) from Yeditepe University. Research Interests Dr. Aydın's scholarly work centers on Improving energy efficiency through building envelope optimization Adaptive reuse of historic structures with sustainability protocols Urban renewal dynamics, particularly in Fikirtepe projects Thermal comfort analysis in educational and residential buildings Project delay mitigation in construction management Integration of BIM and AI for sustainable retrofitting Publication Trends reveal a focus on energy performance (25% of output), adaptive reuse (20%), and project management (18%). His work appears in journals like Energy and Buildings , Buildings , and Sustainability , with increasing emphasis on circular economy principles since 2023. Scientific Recognition He has received: Prosteel 2012 Third Place Prize for 'Modular Bus Terminal Design' Akçansa Betonik Ideas Competition 2011 Shortlist for 'Green Module Design' Repeated peer-review invitations for Journal of Building Engineering (Q1) and others Administrative Contributions Currently serves on: Faculty of Architecture Construction and Environment Commission (2024-) Faculty of Architecture Competition Commission (2024-) Department of Architecture Internship Commission (2023-2024) Accreditation Commission membership (2018-2024)

Baran Kaynakمشاهده پروفایل

استادیار

• Cloud Manufacturing
• Blockchain Technology
• Resource Allocation
• +۵ مورد دیگر

Baran Kaynak serves as an Assistant Professor in the Department of Information Systems Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has held academic positions since 2013 (promoted from Lecturer to Assistant Professor in 2022). His institutional affiliation spans teaching, research, and project leadership within Turkey's higher education framework. His educational trajectory culminates in a Doctorate in Industrial Engineering from Sakarya University (2012-2021) with thesis work on Blockchain-Based Cloud Manufacturing Model , preceded by a Master's degree (2011-2013) focusing on wireless sensor networks in manufacturing logistics and a Bachelor's in Industrial Engineering (2007-2011) from the same institution. Dr. Kaynak's research integrates cloud computing, blockchain, and AI to solve industrial and environmental challenges. Core contributions include hybrid decision support systems for cloud manufacturing resource allocation using genetic algorithms and AHP, GPU-accelerated solar potential analysis tools, and custom web components for earth science data (e.g., Geo-WC for NOAA/USGS integration). His work bridges theoretical algorithms with practical implementations in manufacturing, renewable energy, and hydrological systems. Recent publications (2023-2025) reveal expanding applications: digital twin frameworks for urban flood analysis, IoT platforms for hydrological education (HydroSignal), and mmWave sensor-based anomaly detection in assembly lines. These works consistently demonstrate cross-disciplinary innovation, particularly in adapting blockchain for secure resource sharing and developing real-time analytics for environmental monitoring. He leads the UZEP project (2020), a Sakarya University-funded cloud-based distance education platform developed during the pandemic. While no formal student advisees are listed, his research includes student consultancy services using AI for course grade prediction and adaptive neuro-fuzzy systems for academic success modeling. Dr. Kaynak collaborates with Sakarya University's Distance Education Research and Application Center and contributes to open-source tools for earth science organizations. His current work focuses on city-scale digital twins for climate resilience and blockchain-enhanced manufacturing ecosystems, positioning him at the intersection of industrial informatics and sustainable technology development.

• Biomedical Engineering
• Bioelectronics
• Artificial Intelligence
• +۳ مورد دیگر

Rüştü Murat Demirer serves as an Assistant Professor in the Department of Electrical and Electronics Engineering at Işık University's Faculty of Engineering and Natural Sciences. His academic career spans decades with active teaching responsibilities including Biomedical Engineering courses such as Clinical Care Informatics, Biosignal Processing, and Medical Imaging since at least 2012 across multiple institutions including Işık University and Bahçeşehir University. His educational foundation includes: PhD in Biomedical Engineering from Boğaziçi University (1983-2002) MS in Energy from Istanbul Technical University (1980-1982) BS in Electronics and Communications Engineering from Kocaeli University (1976-1980) Dr. Demirer's research integrates Biomedical Engineering with cutting-edge computational neuroscience, focusing on Bioelectronics, Artificial Intelligence applications, and Neuroscience. He pioneers methodologies for analyzing brain dynamics through EEG/ECoG signal processing, entropy-based biomarker development, and machine learning algorithms for neurological and psychiatric conditions. His work bridges theoretical neuroscience with clinical applications in epilepsy, bipolar disorder, and brain-computer interfaces. Analysis of his publication trends reveals strong interdisciplinary convergence between neuroscience, biomedical engineering, and artificial intelligence. Key methodological themes include Hilbert transform applications, nonlinear dynamics in brain signals, entropy quantification for psychiatric diagnostics, and hybrid machine learning approaches for medical signal classification. This research trajectory demonstrates consistent innovation in translating complex brain signal analysis into clinically relevant diagnostic tools. Dr. Demirer has actively mentored 11 graduate students (10 Master's and 1 PhD) between 2013-2025. His advisees' research spans diverse applications including: Machine learning for cybersecurity threat detection Cryptocurrency market analysis using predictive modeling EEG/eye-tracking fusion for cognitive decision studies Medical diagnostics through convolutional neural networks Natural language processing for offensive language detection He maintains professional engagement as a member of the Chamber of Electrical Engineers (Elektrik Mühendisleri Odası) while teaching specialized courses across biomedical engineering, cybersecurity, and data science domains.

• Solar Energy
• Renewable Energy Systems
• Thermal Energy Storage
• +۷ مورد دیگر

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)

Deniz Yuretمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Deniz Yuret is a Professor in the Department of Computer Engineering at Koç University , Istanbul, and the founding director of the KUIS AI Center . Previously, he spent 12 years at the MIT AI Lab and co-founded Inquira, Inc. His research focuses on Natural Language Processing and Machine Learning , with significant contributions in dependency parsing , language modeling , grounded language learning , and character-level NLP . He has pioneered frameworks like Knet , a deep learning library in Julia, and AutoGrad.jl for automatic differentiation. Deniz's academic work spans neural architectures for language-robot interaction, transfer learning in low-resource NMT, and context embeddings for grammatical category acquisition. His recent publications emphasize transformer models , multimodal systems , and efficient language modeling . He has supervised multiple graduate students, including Emre Can Açıkgöz (PhD, UIUC), Onur Kuru (M.S. 2016), Saman Zia (M.S. 2016), and Osman Baskaya (M.S. 2015). His projects include the TUBITAK 1001 (2016-2018) and ReGROUND (2015-2018) in collaboration with international institutions.

Ali Karakusمشاهده پروفایل

دانشیار

• Computational fluid dynamics
• High-level continuous and discontinuous finite elements
• Multiphase flow
• +۵ مورد دیگر

Ali Karakus is an Associate Professor at Middle East Technical University (METU) and Deputy Head of Department. He obtained his Bachelor's degree (2005), Master's degree (2009), and PhD (2015) from METU. His research focuses on computational fluid dynamics, high-order numerical algorithms, and GPU-accelerated solvers for multiphysics problems. Specializes in high-performance scientific computing and finite element methods. Develops GPU-optimized solvers for compressible/incompressible flows, level-set reinitialization, and physics-informed neural networks. The Accelerated Multiphysics (AMiP) research group, led by Dr. Karakus, emphasizes discontinuous Galerkin approaches, adaptive mesh refinement , and Jacobian-free Newton-Krylov methods . His recent work integrates data-driven modeling with traditional fluid dynamics solvers. Notable scientific achievements include: 2024 Lecturer of the Year award from METU Parlar Foundation Collaborative publications on NekRS , a GPU-accelerated Navier-Stokes solver Selected as a groundbreaking paper in Parallel Computing journal Dr. Karakus has supervised multiple M.Sc. theses on topics including: High-order Boltzmann solutions for low Mach aerodynamics Physics-informed neural networks in CFD GPU-accelerated level-set reinitialization His publications demonstrate expertise in GPU parallelization , mesh deformation , and weakly compressible flow modeling .

Mustafa Tosunمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Artificial Neural Networks
• Deep Learning Algorithms
• +۶ مورد دیگر

Assoc. Prof. Dr. Mustafa Tosun is a faculty member at Simav Faculty of Technology, Dumlupinar University, where he serves in the Department of Electrical-Electronic Engineering. With a PhD in Electrical and Electronic Engineering from Sakarya University, he has established himself as a researcher specializing in the application of artificial intelligence to biomedical signal processing. His educational background includes a Bachelor's degree in Electrical-Electronic Engineering from Selcuk University (1988-1992), followed by a Master's degree from Dumlupinar University (1994-1997), and ultimately his doctorate from Sakarya University (1998-2004). Prior to his current academic position, he gained valuable industry experience working at Turk Telekom Inc. from 1999-2006 in the Information Networks Directorate. Professor Tosun's research primarily focuses on Artificial Intelligence applications in biomedical engineering , with special emphasis on EEG signal processing using deep learning techniques. His work spans multiple domains including Brain Computer Interfaces, cognitive workload measurement, pain threshold estimation, and neurological disorder classification. He has published extensively in these areas, with a notable increase in publications during 2020-2022. His recent publications demonstrate a strong trend toward applying advanced machine learning techniques to solve complex biomedical problems, particularly in EEG signal analysis and classification. The research shows consistent focus on improving signal processing methods, artifact removal, and developing more accurate classification systems for various medical applications. As an educator, Professor Tosun teaches a wide range of courses including: Fundamentals of Biomedical Engineering Fuzzy Logic Introduction to Electrical and Electronics Engineering Electronics I & II Artificial Neural Networks Neural Networks and Deep Learning He actively supervises graduate students, with numerous ongoing and completed theses in areas such as EEG-based psychiatric disease investigation, brain-computer interfaces, and pain classification systems. His research group appears well-established with multiple concurrent projects addressing different aspects of AI applications in biomedical engineering.

Burak Yildirimمشاهده پروفایل

دانشیار

• Power Systems
• Renewable Energy Integration
• Microgrid Control
• +۵ مورد دیگر

Burak Yildirim serves as Associate Professor in the Department of Electronics and Automation at Bingöl University's Technical Sciences Vocational School since 2022, following 11 years as Teaching Staff. His academic foundation includes BSc, MSc, and PhD degrees in Electrical-Electronics Engineering from Fırat University. BSc: Electrical-Electronics Engineering, Fırat University (2002-2006) MSc: Electrical-Electronics Engineering, Tunceli University (2010-2013) PhD: Electrical-Electronics Engineering, Fırat University (2013-2017) His research bridges theoretical control systems and practical energy applications, focusing on microgrid stability , AI-enhanced frequency regulation , and renewable integration . Recent work explores cybersecurity for energy systems and digital twin applications, with 15+ publications in SCI journals since 2020 including International Journal of Hydrogen Energy and IEEE Transactions. Dr. Yildirim's publication trends show increasing sophistication in control methodologies, evolving from traditional PID controllers (2018-2020) to neuromorphic deep learning and multi-agent systems (2022-2024). His work consistently addresses low-inertia grid challenges, with 70% of recent publications incorporating AI techniques for stability enhancement. He actively secures research funding through international collaborations and TUBITAK grants, currently leading projects on digital twins for microgrid controllers and HiL technology for next-generation power electronics. His industry background in high-voltage systems informs his applied research approach. Teaching responsibilities span core electronics and power systems courses, with recent emphasis on RF techniques and digital design applications. His industry experience (2007-2011) in transmission infrastructure provides practical context for academic instruction.

Olivier Roustantمشاهده پروفایل

استاد

• Probability and statistics
• Statistical/machine learning
• Artificial intelligence
• +۶ مورد دیگر

Olivier Roustant is a Full Professor in Applied Mathematics at INSA Toulouse and a member of the Institut de Mathématiques de Toulouse. His academic career spans from teaching in French high schools to his current position as a leading researcher in mathematical engineering. His research interests focus on probability and statistics, statistical/machine learning, and artificial intelligence, with specific expertise in stochastic modeling, global sensitivity analysis, and computer experiments. Professor Roustant's work on small data analysis has practical applications in complex modeling scenarios. Co-PI of the ANITI Chair PILearnWater 'Physics-informed learning methods for continental waters and marine risks' Associate editor of SIAM/ASA Journal on Uncertainty Quantification Co-director of the double-degree by apprenticeship ModIA program Professor Roustant has received notable recognition including the 2013 ENBIS Greenfield Challenge (as co-winner) and the 2010 ENBIS Young statistician award. His teaching focuses on mathematics for engineers at L3, M1, and M2 levels, with an emphasis on problem-guided projects and practical data science applications.