جستجوی استاد راهنمای دانشگاهی

Figen S. Oktem is an Associate Professor in the Department of Electrical and Electronics Engineering at Middle East Technical University (METU), Ankara, Turkey. Her research focuses on advanced imaging systems and algorithms, including computational imaging, inverse problems, and machine learning applications in signal processing. Ph.D., Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (UIUC) (2014) M.S., Electrical and Electronics Engineering, Bilkent University (2009) B.S., Electrical and Electronics Engineering, Bilkent University (2007) Her work bridges physics-informed machine learning and computational optics, with applications in spectral imaging, radar, and microwave systems. She has also explored Fourier phase retrieval, denoising diffusion models, and real-time MIMO radar imaging. Recent publications highlight trends in phase retrieval using deep learning ( prNet , I2I-PR , DDRM-PR ), 3D MIMO imaging, and compressive spectral imaging. Techniques often integrate plug-and-play regularization, stochastic refinement, and physics-based priors. She can be contacted via email at figeno@metu.edu.tr . Curriculum vitae and publications are accessible through her Google Scholar profile.

• Computational Imaging
• Physics-informed Machine Learning
• Inverse Problems
• +۵ مورد دیگر

Tayfun Akgül is a Professor at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, Department of Electronics and Communication Engineering. With academic affiliations spanning decades, he combines engineering rigor with innovative research in signal processing and underwater acoustics. His research focuses on advanced signal processing techniques, including Compressive sensing and cyclostationary analysis Underwater acoustic monitoring and sensor arrays Thermal imaging and infrared reflection modeling Biometric identification through facial attributes Seismic signal processing Recent publications demonstrate expertise in Propeller noise analysis in maritime environments Micro-Doppler helicopter signature detection Seismic activity precursor identification Novel fisheye camera human detection systems Awarded Most Successful Doctoral Thesis Award from TESID (2024) IEEE Top 10 Award (2013) he maintains active IEEE membership since 1992 and has led multiple high-impact projects including casualty detection systems and electric vehicle warning systems.

• Image Processing
• Signal Processing
• Audio and Speech Processing
• +۵ مورد دیگر

Semih Doğu is an Assistant Professor at the Department of Electronics and Communication Engineering , Faculty of Electrical and Electronics Engineering , Istanbul Technical University . His research focuses on Electromagnetic Theory , Microwave Imaging , Inverse Scattering Problems , and Antenna Design . Doctorate: Istanbul Technical University (2023) Master's: Istanbul Technical University (2017) Bachelor's: Yıldız Technical University (2015) His research interests emphasize microwave-based diagnostics, including: Microwave imaging for breast cancer detection Antenna optimization for medical and security applications Inverse problem solving in electromagnetic systems Through-the-wall imaging for surveillance Semih Doğu's recent publications demonstrate his expertise in: Neural networks for temperature monitoring in hyperthermia Ku/Ka-band antenna designs for satellite systems Microwave salinity sensing Algorithm development for improved imaging accuracy He contributes to the ITU Electromagnetics Research Group , participating in projects like: Microwave Brain and Breast Imaging Device Development Compressed Sensing for Energy-Efficient Communication Microwave Tissue Analysis

• Electromagnetic Theory
• Microwave Imaging
• Inverse Scattering Problems
• +۳ مورد دیگر

Assoc. Prof. Dr. Hakan Tunçdemir is an Associate Professor at the Department of Mining Engineering, Istanbul Technical University (ITU), Faculty of Mining. He holds a PhD in Mining Engineering from ITU (2002) and has over 25 years of academic and industry experience in mining and rock mechanics. Educational Background: Bachelor’s in Mining Engineering, ITU (1994) Master’s in Mine Excavation and Mechanization, ITU (1996) PhD in Mining Engineering, ITU (2002) Research Interests focus on: Rock mechanics and mine system analysis Numerical modeling of mining systems Geostatistical applications in mining Advanced tunneling technologies and slope stability Shotcrete behavior and mine support systems Key Projects include: Analysis of tunnel support pressures using FEM InSAR-based slope instability monitoring in open pits Development of shotcrete-rock interaction models Recipient of the 2007 Mining Scientific Incentive Award from the Chamber of Mining Engineers Istanbul Branch. Active member of international societies including International Society of Rock Mechanics and Society of Mining Metallurgy.

• Mining Methods
• Rock Mechanics
• Excavation Mechanics
• +۴ مورد دیگر

Gökberk Cinbiş is an Associate Professor at the Department of Computer Engineering, Middle East Technical University (METU), leading research in data-efficient machine learning with minimal supervision. His work spans zero-shot, few-shot, weakly-supervised, and self-supervised learning, with applications in vision-language integration and large-scale image/video understanding. PhD from Université de Grenoble (2014) M.A. from Boston University (2010) His research focuses on generative models, meta-learning, and robust computer vision systems. Recent work explores sparsity in parameter-efficient fine-tuning, token embeddings for vocabulary extension, and domain-aware LoRA components for personalization. Notable trends in his publications include: Advancements in zero-shot and few-shot learning Applications in remote sensing (SAR2ET for evapotranspiration) Meta-learning and hybrid augmentation techniques Sign language recognition and industrial vision benchmarks Scientific honors include: Science Academy - Young Scientist Award (BAGEP 2024) Google Faculty Research Award (2019-2020) Best PhD Thesis Prize by AFRIF (2015) Alper Atalay Best Student Paper Award (2016) He has supervised MSc students Gencer Sumbul and Berkan Demirel, secured TUBITAK grants on meta-learning and any-shot learning, and organized workshops on industrial inspection at CVPR and ECCV. Cinbiş leads METU ImageLab, focusing on computer vision and machine learning.

• data-efficient machine learning
• few-shot learning
• zero-shot learning
• +۶ مورد دیگر

Serkan KESER is an Associate Professor in the Department of Electrical and Electronics Engineering at the Faculty of Engineering and Architecture, Ahi Evran University, Turkey. He has been serving as a full-time faculty member since 2018 and previously served as Head of Department from 2018-2021. His educational background includes a PhD in Electrical and Electronics Engineering from Eskişehir Osmangazi University (2009-2018), a Master's degree in the same field from the same institution (2005-2008), and a Bachelor's degree in Electrical and Electronics Engineering from Mustafa Kemal University (1999-2005). Dr. KESER's research focuses on three main areas: Audio and Speech Processing : Including speaker identification, isolated word recognition, and speech coding techniques Signal Processing : With applications in fiber optic sensor systems and acoustic positioning Image Processing : Covering face recognition, image compression, and denoising techniques His recent publications demonstrate a strong trend toward integrating machine learning and deep learning approaches with traditional signal processing methods. He has made significant contributions in applying subspace methods to various domains including speech recognition, image processing, and sensor technologies. His work often bridges theoretical signal processing concepts with practical applications in areas like smart home systems, medical imaging, and environmental monitoring. Dr. KESER has successfully supervised five Master's students to completion, with thesis topics spanning deep learning applications for class attendance systems, photovoltaic systems, speaker identification, brain tumor classification, and speech-controlled robotic arms. He has led four research projects, including development of fiber optic motion sensors, smart home models using Arduino microcontrollers, and science outreach initiatives. His teaching portfolio includes advanced courses in digital image processing, artificial neural networks, digital signal processing, and machine learning at both undergraduate and graduate levels. Dr. KESER's research impact is reflected in his publication metrics: 30 total publications with 117 citations (h-index 5) through the UNIS system, 25 publications with 180 citations (h-index 6) on Google Scholar, and strong representation in Scopus and Web of Science databases.

• Audio and Speech Processing
• Signal Processing
• Image Processing
• +۳ مورد دیگر

Prof. Tanju YELKENCİ is an academic who continues his work in electromagnetic theory and forward and inverse scattering problems within the Faculty of Engineering , Department of Electrical and Electronics Engineering . His research bridges theoretical electromagnetics with practical applications in radiation safety and computational modeling. Education Licence (1982-1986): Yıldız Technical University, Department of Electrical Engineering. Master's (1986-1989): Istanbul Technical University, Electronics and Communications Program. Doctorate (1994-1999): Technische Universitaet Wien (Vienna Technical University), Faculty of Electrotechnics. His research focuses on numerical methods in electromagnetics , including specific absorption rate (SAR) analysis for mobile phone radiation, inverse scattering problems in complex geometries, and electromagnetic safety standards . Recent publications highlight his work on computational models for iron slags and inverse scattering in waveguide structures .

• Electromagnetic Theory
• Inverse Scattering Problems
• Computational Electromagnetics
• +۳ مورد دیگر

Cihan Bayındır is an Associate Professor at Istanbul Technical University's Faculty of Civil Engineering, Department of Civil Engineering, specializing in fluid mechanics, coastal engineering, and computational methods. His research integrates advanced mathematical techniques with practical engineering applications across multiple disciplines. His primary research areas include Fluid Mechanics, Coastal Sciences and Engineering, Numerical Modeling, Fluid Physics, Acoustics and Vibrations, Nonlinear Dynamics, and Quantum Hydrodynamics. Bayındır's work demonstrates a strong interdisciplinary approach, bridging traditional civil engineering with cutting-edge computational methods and quantum phenomena. His research has significant applications in coastal protection, renewable energy systems, disaster management, and infrastructure resilience. Analysis of his recent publications reveals a clear trend toward applying artificial intelligence and machine learning techniques to traditional civil engineering challenges. His work increasingly focuses on using compressive sensing, deep learning (particularly LSTM networks), and fuzzy logic systems to solve complex problems in wave dynamics, vibration analysis, and tsunami prediction. The integration of quantum computing concepts with classical fluid mechanics represents another distinctive aspect of his research portfolio. ITU Doctoral Special Award-2024-Advisor (2025) ITU 2023 Academic Performance Award (2024) Turkish Academy of Sciences (TUBA) Outstanding Young Scientist Award (GEBİP) (2022) Elsevier Frontiers Article Award (2020) Kaleidoscope Award (American Physical Society, 2016) Bayındır leads multiple research projects funded by ITU's Scientific Research Projects Unit (BAP), including studies on dam break wave propagation using fractional equations, optimization of wave energy concentrators with AI methods, and three-dimensional vibration control in marine structures. His work involves collaborations with international institutions, including previous engagement with CERN on accelerator design. He maintains an active research laboratory focused on hydraulics and coastal engineering, with specialized equipment for wave and vibration analysis in the Hydraulics Laboratory HL 216 at ITU.

• Fluid Mechanics
• Coastal Sciences and Engineering
• Numerical Modeling
• +۱۵ مورد دیگر

Professor Sema Kayhan is a faculty member at Gaziantep University , Faculty of Engineering , Department of Electrical and Electronic Engineering . She has held the academic rank of Professor since 2021, after progressing from Associate Professor (2016-2021) and Assistant Professor (2007-2015). Her career began at Gaziantep University as a Research Assistant (1996-2005) and includes administrative roles as Vice Head of Department (2013-2015). Doctorate: 1999-2005, Gaziantep University Institute of Science, Electrical and Electronic Engineering Degree: 1996-1999, Gaziantep University Faculty of Engineering, Electrical and Electronic Engineering & Computer Science Licence: 1991-1996, Gaziantep University Faculty of Engineering, Electrical and Electronics Engineering (English) Her research spans Image Processing , Compressive Sensing , Machine Learning , and Biomedical Signal Processing , with notable contributions to ECG signal reconstruction , chaotic encryption , and FPGA-based hardware acceleration . She has supervised 23 theses, including PhD works on hybrid deep learning for schizophrenia detection , sparse extreme learning machines , and smart home solar energy systems . Her 15 most recent publications (2015-2022) demonstrate expertise in image watermarking , encryption , antenna design , and ECG signal processing , often leveraging chaos theory , extreme learning machines , and FPGA implementations . She has also contributed to NLP for Arabic-alphabet languages and retinal blood vessel segmentation via transfer learning. Professor Kayhan's projects include renewing jacquard control systems (2007-2008) and ECG signal reconstruction via compressive sensing on FPGA (2016-2017). She co-designed a smart home model using solar energy (2017) and has been a Member of the Chamber of Electrical Engineers since 1997.

• Image Processing
• Compressive Sensing
• Signal Processing
• +۱۱ مورد دیگر

Mehmet Demir is an Assistant Professor at Gaziantep University, Faculty of Engineering, specializing in Electrical and Electronics Engineering. His research focuses on signal processing, image processing, and machine learning with applications in synthetic aperture radar (SAR) imaging and compressed sensing. Education: PhD (2013-2019), MSc (2009-2012), and BSc (2004-2009) in Electrical and Electronics Engineering at Gaziantep University Academic Positions: Assistant Professor (2021-present), Research Assistant (2013-2021), and Research Assistant (2009-2013) at Gaziantep University Demir's research explores advanced algorithm development for SAR imaging systems, particularly in handling quantized data and signal-translation errors. His work leverages computational methods like ADMM, FISTA, and spectral conjugate gradient techniques, with applications in remote sensing and signal reconstruction. Recent publications focus on 1-bit compressive sensing in SAR imaging (2018, 2019, 2020, 2021), demonstrating his ongoing contributions to data-efficient image reconstruction algorithms. His research has received recognition through TÜBİTAK Publication Incentive Awards in 2019 and 2014. Demir actively engages in scientific communities as a member of TMMOB-EMO (Chamber of Electrical Engineers) since 2009, and contributes to engineering education with courses like EEE439 Introduction to Remote Sensing, emphasizing practical algorithm development in MATLAB/Python.

• Electrical Engineering
• Signal Processing
• Image Processing
• +۳ مورد دیگر

Hande Alemdar is an Assistant Professor at the Department of Computer Engineering, Middle East Technical University, specializing in machine learning, data science, and big data analytics. She earned her BSc, MSc, and PhD in Computer Engineering from Boğaziçi University in 2004, 2009, and 2015, respectively, with her PhD thesis awarded the Bogazici University Research Fund (BAP) Best Thesis Award. PhD in Computer Engineering (2015), Boğaziçi University MSc in Computer Engineering (2009), Boğaziçi University BSc in Computer Engineering (2004), Boğaziçi University Her research focuses on applying machine learning to resource-efficient hardware, wireless sensor networks, and smart environments. She has pioneered work on ternary neural networks for FPGA-based AI, which reduce computational costs while maintaining accuracy. Her work spans diverse applications like activity recognition, fall detection, and sports analytics. Her recent publications reflect trends in deep learning for hardware efficiency, smart healthcare via ambient sensors, and network security with machine learning. These studies often integrate multi-modal sensor fusion and real-time data analysis , emphasizing deployability in resource-constrained scenarios. Scientific Awards Bogazici University BAP Best Thesis Award Hande has collaborated with Grenoble Informatics Institute and industry leaders like ST Microelectronics on energy-efficient AI. Her work has been published in journals and conferences such as Sensors, Computers & Graphics, and FPL, addressing topics from elite football performance analysis to covert channel detection in SDN. She leads research in scalable architectures for smart environments and is involved in the H2020 FET Project 'ROBOtic Replicants for Optimizing the Yield by Augmenting Living Ecosystems', demonstrating her commitment to interdisciplinary AI applications.

• Machine Learning
• Data Science
• Big Data Analytics
• +۶ مورد دیگر

Tufan Coşkun Karalar is an Associate Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University (ITU), College of Engineering. His research spans integrated circuits, analog-to-digital converters, wireless sensor networks, and energy-efficient electronic systems. He is actively involved in advanced IC design projects for applications in biomedical implants, green energy, and automotive communications. Research Interests: Integrated and analog circuit design High-speed data converters (ADCs) In-memory computing architectures RF front-end and V2X communication circuits Low-power and energy-efficient sensor networks Hall effect and current sensing technologies His recent publications focus on SRAM-based in-memory computing energy models, high-speed pipelined ADCs, and RF front-end modules for vehicle-to-everything (V2X) systems. These works reflect a strong trend toward energy efficiency, high performance, and application-specific circuit design in modern electronics. Scientific Awards: ELECO 2019 Best Student Publication Award Dr. Karalar has served as Principal Investigator (PI) on multiple research projects funded by TUBITAK and TTO, including studies on ASIC design, micro-implant power control ICs, high-speed ADCs, and improved Hall effect sensors. He is currently supervising 24 theses, indicating an active role in mentoring graduate students. His work involves close collaboration with industry and academic partners in Turkey and internationally. Labs and Research Teams: While specific lab names are not mentioned, his project leadership and publication record suggest he leads a research group focused on analog and mixed-signal integrated circuit design within the Department of Electronics and Communication Engineering at ITU.

• Integrated Circuits
• Analog-to-Digital Converters
• Wireless Sensor Networks
• +۷ مورد دیگر

Assistant Professor Süha Tuna is affiliated with Istanbul Technical University at the Institute of Informatics in the Computational Science and Engineering department. She holds a postdoctoral degree from the University of Strathclyde and has been actively involved in academic roles since 2010.

• Machine Learning
• Bioinformatics
• Hyperspectral Imaging
• +۲ مورد دیگر

Professor Ender Mete Ekşioğlu serves in the Department of Electrical and Electronics Engineering at Istanbul Technical University, where he has held academic positions since 1999. His current role as Professor began in 2019 following progression from Associate Professor (2013-2019) and Assistant Professor (2005-2012) ranks. PhD in Electronics and Communication Engineering, Istanbul Technical University (2000-2005) Degree from University of Michigan (1994-1997) Additional studies at University of Michigan (1997-1999) Professor Ekşioğlu's research spans Machine Learning, Deep Learning, and advanced Signal Processing with emphasis on medical imaging applications. His work bridges traditional signal processing techniques with modern deep learning approaches, particularly in Magnetic Resonance Image Reconstruction where he applies sparsity principles and neural network architectures. Key focus areas include image denoising, segmentation, and enhancement across medical, underwater, and atmospheric imaging contexts. His publication trends demonstrate consistent innovation in imaging inverse problems, with recent work integrating pixel-level processing with physical modeling in underwater imaging and developing topological awareness for medical image segmentation. The research shows strong continuity between traditional signal processing methods (like DCT) and cutting-edge deep learning architectures. Professor Ekşioğlu has led six significant research projects funded by TUBITAK and BAP, including 'Deep Learning in Image Processing Inverse Problems' and 'Parallel magnetic resonance imaging techniques and applications'. These projects have resulted in substantial research output with applications spanning medical diagnostics to remote sensing. h-index of 13 based on Scopus citations 2000+ total research outputs Active supervision of 27 theses in progress His laboratory work focuses on imaging inverse problems, with particular strength in MRI reconstruction techniques that combine deep learning with recursive algorithms. Current research directions include topological awareness in segmentation networks and hybrid approaches that integrate traditional signal processing with neural networks for improved robustness.

• Machine Learning
• Deep Learning
• Signal Processing
• +۷ مورد دیگر

Merve Erdal is an Associate Professor in the Department of Mechanical Engineering at Middle East Technical University (METU), Ankara, Turkey. She holds a B.Sc. (1989), M.Sc. (1992) from METU, and a Ph.D. (1998) from the University of Illinois. Her research focuses on transport phenomena in materials processing, composites, structural/functional ceramics, rapid prototyping, and computational fluid mechanics. She leads the Composites Lab, offering graduate research opportunities in vascularized composites, electrically conductive materials, honeycomb structures, and microstructure control in composites. Her work emphasizes advanced manufacturing techniques like selective laser sintering and resin transfer molding. Notable projects include strain monitoring systems in fiber-reinforced composites, CNT dispersion effects, and optimization of sandwich structures. Her research bridges material science with mechanical engineering, addressing challenges in composite design, process-induced defects, and material functionality. Current research topics include: 1) Controlled functionality in composites via vascularized designs, 2) Electrically conductive nanocomposites, 3) Honeycomb sandwich structure processing, and 4) Microstructure homogenization through resin flow control. She collaborates on numerical modeling of void dynamics, warpage characterization, and equivalent material models for sandwich laminates. Dr. Erdal’s publications span journals like Advanced Composite Materials , Results in Physics , and Journal of Composite Materials , reflecting her expertise in composite mechanics, material characterization, and process simulation. Open positions are available for graduate students in her lab, focusing on innovative composite applications and advanced manufacturing processes.

• Transport Phenomena in Materials Processing
• Composites
• Structural/Functional Ceramics
• +۵ مورد دیگر