جستجوی استاد راهنمای دانشگاهی

Ozcan Ozturk is a Professor in the Computer Science and Engineering and Electronics Engineering programs at Sabancı University's Faculty of Engineering and Natural Sciences. Previously, he held professorships at Bilkent University and adjunct roles at North Carolina State University. His expertise spans heterogeneous computing, parallel systems, processor architecture, and compiler optimization. He earned his Ph.D. from Penn State University, with prior academic roles at the University of Florida and internships at Intel and Marvell. Education: Ph.D. in Computer Science and Engineering (2007), Pennsylvania State University M.S. in Computer Engineering (2002), University of Florida B.Sc. in Computer Engineering (2000), Bogazici University Research interests include accelerator technologies, GPU-based systems, multicore processors, and compiler optimizations. His work focuses on improving parallelization efficiency, energy optimization, and reliability in heterogeneous architectures. He leads funded projects like 'Machine Learning for Compiler Flags' and 'Graph Accelerator Design'. Notable awards include the Bilkent Teaching Award (2019), BAGEP (2018), and HiPEAC Paper Award (2016). He serves on editorial boards of IEEE and ACM journals and chairs major conferences like ASPLOS and ICS. Grants and collaborations include partnerships with Huawei, Intel, NVIDIA, and TÜBİTAK. He advises over 20 students and has supervised projects in safety-critical systems, FPGA accelerators, and compiler-directed optimizations. His lab develops domain-specific architectures, including RISC-V extensions for graph processing.

• Heterogeneous Computing
• Hardware Accelerators
• GPU Computing
• +۷ مورد دیگر

Prof. Dr. Ahmet ÖZMEN is a Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Software Engineering. He has held various administrative positions including Head of the Software Engineering Department (2019-2028) and Director of the Computer Research and Application Center (2019-2022). With extensive experience in academia since 1991, he has made significant contributions to computer vision, traffic monitoring systems, and sensor technologies. Sakarya University: Professor (2019-present), Associate Professor (2011-2019) Dumlupınar University: Assistant Professor (2001-2011), Research Assistant (2000-2001, 1993-1998) Istanbul Technical University: Research Assistant (1991-1993) Prof. ÖZMEN's research spans computer vision applications for traffic monitoring, indoor air quality systems, parallel computing, and sensor technologies. His work bridges theoretical computer science with practical engineering applications, particularly in developing vision-based systems for nighttime vehicle detection, traffic flow monitoring, and environmental sensing. His interdisciplinary approach combines machine learning, image processing, and embedded systems to solve real-world problems in transportation and environmental monitoring. His publication record shows a clear evolution from parallel and distributed systems in his early career to computer vision and sensor applications in recent years. The majority of his recent work focuses on traffic monitoring systems using computer vision techniques, particularly for nighttime conditions, and indoor air quality monitoring systems using sensor networks. His research demonstrates strong industry and societal relevance, with applications in smart transportation, environmental protection, and educational technology. TÜBİTAK Publication Awards (2006, 2008, 2009, 2010) Physical implementation award from TÜBİDER (2008) Microsoft Certified Professional Certificate (2005) YÖK overseas study scholarships (1993, 1998) Elginkan graduate scholarships (1990, 1991) Prof. ÖZMEN has supervised numerous graduate students across multiple institutions, with a focus on practical engineering problems. His research has been supported by various projects including TÜBİTAK projects, institutional research grants, and industry collaborations. He has led significant research initiatives in traffic monitoring systems, indoor air quality monitoring, and educational technology platforms. His administrative leadership has included directing research centers and shaping curriculum development in software engineering. His work has involved establishing research teams focused on computer vision applications, sensor network development, and educational technology. These teams have produced numerous publications, developed practical systems, and trained the next generation of computer engineers. Current research directions include advanced traffic monitoring systems using deep learning and multi-camera setups for urban planning applications.

• Computer Vision
• Traffic Monitoring Systems
• Sensor Systems
• +۶ مورد دیگر

Selin Aslan serves as an Assistant Professor in the Department of Mathematics at Koç University, Istanbul, Turkey, where she conducts research at the intersection of computational mathematics and imaging science. Her academic appointments and research activities are centered within the university's mathematics department, contributing to both undergraduate and graduate education in mathematical sciences. Her educational qualifications include: PhD in Mathematics from Virginia Polytechnic Institute and State University (2018) Master's in Mathematics from Rochester Institute of Technology (2013) B.A. in Mathematics from Ege University (2010) Dr. Aslan's research program focuses on developing advanced computational methods for solving inverse problems in imaging, with particular expertise in phase retrieval, tomographic reconstruction, and ptychography. Her work bridges theoretical mathematics with practical applications in medical imaging, microscopy, and materials science, emphasizing algorithmic innovation and computational efficiency. She integrates techniques from deep learning, optimization theory, and high-performance computing to address challenges in image reconstruction under physical constraints. Analysis of her publication record reveals a consistent trajectory toward solving complex imaging problems through hybrid approaches that combine physics-based models with data-driven techniques. Her recent work demonstrates increasing emphasis on scalability for large datasets, robustness in photon-limited scenarios, and real-time processing capabilities, with applications spanning biomedical imaging to advanced microscopy. No scientific awards were documented in the available sources. Information regarding student advising and research grant activities was not specified in the provided materials, though her publication record suggests active research collaboration. Her computational focus implies engagement with high-performance computing resources for large-scale image reconstruction tasks. While specific laboratory infrastructure details were unavailable, her research on multi-GPU implementations and distributed computing indicates utilization of advanced computational facilities for handling large-scale imaging datasets.

• Applied Mathematics
• Computational Mathematics
• Imaging Science
• +۲ مورد دیگر

Gülay YALÇIN is an Assistant Professor at Abdullah Gul University since 2016. Prior to this, she held a post-doctoral position at the Barcelona Supercomputing Center (BSC) from 2014-2015 and was a researcher there from 2009-2014. She obtained her Ph.D. from Universitat Politècnica de Catalunya in 2014, focusing on Computer Architecture. Her academic background also includes an M.S. from TOBB University (2007) and a B.S. from Hacettepe University (2003), both in Computer Engineering. Education: Ph.D.: Universitat Politècnica de Catalunya, Department of Computer Architecture (2008-2014) M.S.: TOBB University of Economics and Technology, Computer Engineering (2007) B.S.: Hacettepe University, Computer Engineering (2003) Research Interests: Computer Architecture Reliable Computer Design Fault Detection and Recovery Parallel Computer Architectures Hardware Transactional Memory Low-Power Designs Her work emphasizes improving system reliability through innovative fault tolerance mechanisms and energy-efficient computing solutions. Scientific Awards: ParaDIME Project Shortlisted for the 2016 Innovation Radar Prize Advising and Projects: Supervised: Albert Njoroge Kahira (M.S. Candidate) on "Designing Reliable Microarchitectures According to Application Requirements" Project Roles: Researcher in ParaDIME (2012-2015) and Velox (2008-2011)

• Computer Architecture
• Reliable Computer Design
• Fault Detection and Recovery
• +۳ مورد دیگر

Muammer Altan Çakır is a Professor in the Department of Physics Engineering at Istanbul Technical University, actively engaged in high-energy physics research with significant contributions to the CMS Collaboration at CERN. His work focuses on proton-proton collisions, Higgs boson physics, and top quark studies using Large Hadron Collider data. His research interests span experimental particle physics with emphasis on proton-proton collisions , Higgs boson characterization , lepton physics , and transverse momentum analysis . Recent work explores charm baryon production, Drell-Yan processes, and muon identification techniques using advanced multivariate methods in the CMS detector. Analysis of his 15 most recent publications reveals a strong focus on precision measurements in high-energy collisions, particularly in Higgs physics (3 publications), top quark physics (2), and detector optimization (2). His work consistently addresses fundamental questions in the Standard Model through advanced statistical techniques and large-scale data analysis. Doktora sonrası araştırma bursu (2010) Landes Baden Württenberg Doktorarbeit Stipendium (2006) LPC Fall Guest Visitor Faculty (2017) Multiple Performans ödülü awards (2012, 2013, 2015) Professor Çakır has supervised 15 students and leads multiple research projects including GPU-based distributed computing platforms for big data processing, real-time predictive maintenance systems, and deep learning applications for top quark spin correlation studies. His current projects integrate generative AI with domain-specific physics research while developing scalable open-source big data architectures for industrial applications. His laboratory work centers on CMS detector data analysis, with recent focus on online data visualization tools and multivariate techniques for particle identification. Current projects explore GPU-accelerated computing frameworks and generative AI applications for physics-informed design systems.

• High-Energy Physics
• Particle Physics
• Proton-Proton Collisions
• +۵ مورد دیگر

Ali Karakuş is an Associate Professor of Mechanical Engineering at the Middle East Technical University (METU) in Ankara, Turkey. His research focuses on computational fluid dynamics, high-order numerical methods, multiphase flows, and GPU-accelerated scientific computing. He leads the Accelerated Multiphysics (AMiP) research group, which develops advanced algorithms for multiphysics problems using modern parallel architectures. Education: B.Sc. (2005), M.Sc. (2009, Mersin University), Ph.D. (2015), all from METU. His work emphasizes high-order discontinuous Galerkin methods, physics-informed neural networks, and software development (e.g., libParanumal ). Key achievements include the 2024 Lecturer of the Year Award from the METU Parlar Foundation and recognition of the NekRS solver as a groundbreaking paper in Parallel Computing . He supervises a team of PhD and MSc students working on topics like adaptive mesh refinement, level-set interface capturing, and GPU-accelerated solvers. Recent projects include developing physics-informed neural networks for fluid flow problems and Boltzmann-based methods for compressible flows.

• Computational Fluid Dynamics
• High-Order Finite Element Methods
• Multiphase Flows
• +۵ مورد دیگر

Deniz Turgay Altılar is a Professor in the Department of Computer Engineering at Istanbul Technical University (ITU), Faculty of Computer and Informatics. He has been an active academic since 1988, progressing from Research Assistant to Associate Professor in 2013 and later achieving the rank of Professor. His work is centered on distributed systems, cloud computing, and computer networks, with expanding interests in AI applications for agriculture and healthcare. Education Bachelor of Science, Control and Computer Engineering, Istanbul Technical University (1984–1988) Master of Science, Computer Engineering, Istanbul Technical University (1988–1992) Research experience at Queen Mary and Westfield College, University of London (1998–2002) His research interests include parallel and distributed systems, cloud computing, secure computation, deep learning, and cybersecurity. He applies these to interdisciplinary domains such as corn yield prediction, radar identification, and medical diagnostics using ECG signals. His recent work emphasizes efficient and secure AI systems. The publication trends show a strong focus on distributed deep learning, straggler mitigation, secure multiparty computation, and hardware-based attack detection. His work bridges theoretical computer science with real-world applications in agriculture, medicine, and national security. Recent articles highlight innovation in lightweight AI models, privacy-preserving computation, and cross-layer system design. Scientific Awards No specific awards are mentioned in the provided text. He actively supervises students and leads major research projects, including those on cache side-channel attacks in multi-tenant clouds, distributed OpenCL platforms, real-time scheduling, and molecular communication in nano-networks. These projects reflect sustained external funding and leadership in cutting-edge computing domains. His research group collaborates across disciplines and institutions, contributing to both national and international scientific communities. Labs and Teams : While not explicitly named, his role as Principal Investigator on multiple projects suggests leadership in a research lab focused on distributed systems, cybersecurity, and applied AI at ITU.

• Parallel and Distributed Systems
• Cloud Computing
• Computer and Communication Networks
• +۱۲ مورد دیگر

Prof. İbrahim Aydoğdu is an Associate Professor at Akdeniz University, Faculty of Engineering, Department of Civil Engineering , with a concurrent Associate Professor role at Georgia Institute of Technology, Engineering Faculty, Mechanical Engineering . His career spans structural engineering, metaheuristic optimization, and thermohydraulic systems. PhD in Engineering Sciences from Middle East Technical University Postdoctoral research at Georgia Institute of Technology His research focuses on structural optimization , steel and composite structures , and metaheuristic algorithms . He has supervised 13 theses, including projects on seismic isolation, nanoscale beam optimization, and public transport efficiency. His work emphasizes computational methods for structural design, with funded research from TUBITAK and higher education institutions. Key trends in his 96 publications include applications of artificial bee colony algorithms , social spider optimization , and GPU-based parallel programming in civil and mechanical engineering contexts. He has contributed to books on harmony search methods and nature-inspired algorithms in structural design.

• Structural Engineering
• Optimization
• Mechanics of Solid Bodies
• +۵ مورد دیگر

Sümeyye KAYNAK serves as an Assistant Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences. Her academic profile demonstrates interdisciplinary expertise bridging computer science with environmental sustainability and educational technology through computational modeling and data-driven solutions. Her educational foundation includes: Doctorate (2019) from Sakarya University Institute of Science/Computer and Information Engineering with thesis on solar energy potential modeling using 3D data Master's degree (2014) from same institution focusing on AI-based student counseling infrastructure Bachelor's degree (2012) in Computer Engineering from Sakarya University Faculty of Engineering Dr. KAYNAK's research integrates advanced computational methodologies across multiple domains. Her primary focus areas include Artificial Intelligence applications for resource allocation in cloud manufacturing (utilizing genetic algorithms and AHP), Environmental Informatics for flood modeling and hydrological analysis, and Sustainable Energy systems through solar potential estimation tools. Recent work demonstrates significant expansion into geospatial web components for earth science agencies and digital twin frameworks for urban infrastructure resilience, reflecting growing emphasis on climate change adaptation technologies. Publication analysis from 2012-2025 reveals a clear research evolution: early work (2012-2018) concentrated on educational AI systems and solar energy tools, while current output (2023-2025) prioritizes environmental applications with city-scale flood impact modeling, hydroinformatics, and open data frameworks. This trajectory shows increasing sophistication in real-time data analytics and cross-domain integration, particularly between manufacturing systems and environmental monitoring. No scientific awards were documented in the source materials. Regarding academic mentoring, the available documentation contains no references to graduate student supervision or grant-funded research projects. No laboratory affiliations or research team leadership roles were specified in the provided information.

• Artificial Intelligence
• Cloud Computing
• Environmental Informatics
• +۳ مورد دیگر

Dr. Didem Unat is an Associate Professor at Koç University, College of Engineering, Department of Computer Engineering . Her research focuses on High Performance Computing (HPC) , GPU Computing , and Compiler Design , with particular emphasis on data locality optimization, multi-GPU communication, and adaptive mesh refinement. She leads the Parallel and Multicore Computing Lab , driving innovations in exascale co-design and heterogeneous system optimization. ACM SIGHPC Emerging Woman Leader in Technical Computing Award (2021) ERC Starting Grant (1.5M EUR) for the SparCity Project (2025) EuroHPC Grant for Extreme Scale Technologies and Applications (2025) 2025 BAGEP Award (Science Academy) Her work bridges Computer Architecture and Machine Learning , addressing challenges in data locality , multi-GPU systems , and performance portability . Recent publications highlight trends in sparse tensor optimization , asynchronous AMR execution , and compiler support for heterogeneous memory . She has developed tools like ComScribe for intra-node GPU communication analysis and ReuseTracker for multicore reuse distance analysis. Dr. Unat’s research is supported by grants from ERC and EuroHPC , reflecting her leadership in exascale technologies and GPU-centric systems . She contributes to the evolution of tiling abstractions , dynamic LLM training , and lightweight communication detection for modern architectures.

• High Performance Computing (HPC)
• Data Locality
• GPU Computing
• +۷ مورد دیگر

Can Alkan is an Associate Professor in the Department of Computer Engineering at Bilkent University, leading the Alkan Lab for Bioinformatics & Computational Genomics. His research focuses on algorithmic approaches for analyzing genomic data, including structural variation discovery, hardware acceleration, and pangenomics. He holds a Ph.D. and B.Sc. from Bilkent University and a postdoctoral fellowship from the University of Washington. Education: Postdoctoral Fellow at University of Washington (2005-2011), Ph.D. in Computer Science from Case Western Reserve University (2005), B.Sc. in Computer Science from Bilkent University (2000). Research Interests: Combinatorial algorithms for bioinformatics, high-throughput sequencing analysis, structural variation discovery, and hardware/software co-design for genomic workloads. Recent Work: Contributions to tools like mrFAST, TARDIS, and GateKeeper-GPU, advancing genomic sequence analysis and acceleration techniques. Collaborates with global institutions on computational genomics projects.

• Bioinformatics
• Computational Genomics
• Combinatorial Algorithms
• +۵ مورد دیگر

Prof. Dr. İbrahim ÇAYIROĞLU currently holds a full-time Professor position at Karabük University's Faculty of Engineering and Natural Sciences, Department of Mechatronics Engineering. He has served as Department Chair since 2024 and previously held administrative roles including Dean Assistant and Department Chair between 2003-2021. Education: PhD in Mechanical Engineering (2002), Kırıkkale University MSc in Mechanical Engineering (1996), Kırıkkale University BSc in Mechanical Engineering (1991), Istanbul Technical University Research Focus: Specializes in Computer-Aided Design/Manufacturing, Finite Element Analysis, and Machine Dynamics. His work spans robotics, 3D printing optimization, welding technology, and mechanical system simulation. Recent Trends: 2024 publications highlight autonomous robotics, AI-integrated quality control in manufacturing, and advanced finite element analysis. Earlier works focused on SIFT-based object tracking, 3D printing reinforcement, and welding process evaluation. Advising Record: Supervised 11 graduate theses across diverse topics including autonomous robots, composite materials, and 3D printer design. Technical Projects: Led 12 projects between 2007-2023, including TÜBİTAK-funded excavator simulators, composite 3D printers, and automated glass mosaic tiling systems.

• Computer Aided Design and Manufacturing
• Finite Element Analysis
• Machine Theory and Dynamics
• +۳ مورد دیگر

Dr. Alptekin Temizel is a Full Professor at the Graduate School of Informatics, Middle East Technical University (METU), Ankara, Turkey. He leads the METU Deep Learning and Computer Vision Lab (DLCV) and the GPU Research and Education Center. His research focuses on computer vision, deep learning, GPU computing, and medical image analysis. He holds a B.Sc. in Electrical and Electronic Engineering from METU (1999) and a Ph.D. in Computer Vision from the University of Surrey, UK (2006). Affiliations: Executive Board Member, Neuroscience and Neurotechnology Center of Excellence Executive Board Member, METU Center for Image Analysis (OGAM) DLI Certified Instructor and DLI University Ambassador (NVIDIA) Education: B.Sc.: Electrical and Electronic Engineering, METU, Turkey (1999) Ph.D.: Center for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK (2006) Research Interests: Deep Learning & Computer Vision Applications Medical Image Analysis & Healthcare AI Adversarial Machine Learning & Model Security GPU Parallel Computing & System Optimization Federated Learning in Medical Imaging Recent Achievements: 3rd place in Federated Brain Tumor Segmentation (FeTS) Challenge at MICCAI 2021 Developed SAHI package (2M+ downloads) LIMUC dataset for Ulcerative Colitis endoscopy Teaching: MMI 727: Deep Learning: Methods & Applications MMI 713: Applied Parallel Programming on GPU DI 725: Transformers and Attention-Based Deep Networks MMI 712: Machine Learning Systems Design & Deployment

• Computer Vision
• Deep Learning
• GPU Computing
• +۳ مورد دیگر

Kamer Kaya is an Associate Professor at the Faculty of Engineering and Natural Sciences, Sabancı University. He obtained his PhD in 2009 from the Department of Computer Science and Engineering at İhsan Doğramacı Bilkent University, focusing on Threshold Cryptography. His career spans research roles at CERFACS (France) and Ohio State University, where he worked in the HPC Lab and later as a Research Assistant Professor in the Dept. of Biomedical Informatics. Since 2014, he has been affiliated with Sabancı University and founded Dakik Software Technologies in 2018, focusing on R&D projects in blockchain, machine learning, and high-performance computing (HPC). He is actively involved in Sabancı University's Center of Excellence in Data Analytics and COMPUTE. PhD in Threshold Cryptography from Bilkent University (2009) Postdoctoral research at Ohio State University's HPC Lab Founder of Dakik Software Technologies (2018) His research interests include parallel algorithms , sparse data machine learning , graph algorithms , HPC hardware optimization , and cryptography . He collaborates on projects involving GPUs/IPUs for ML applications, blockchain interoperability, and digital twins for automation. As a team leader, he seeks students skilled in algorithms, data structures, and C/C++ programming.

• Parallel Algorithms
• Machine Learning on Sparse Data
• Graph Algorithms
• +۶ مورد دیگر

Ayşe Yılmazer Metin is an Assistant Professor in the Department of Computer Engineering at Istanbul Technical University's Faculty of Computer and Informatics. Her research focuses on computer architecture, GPU computing, and hardware security, with significant contributions to parallel processing systems and cryptographic implementations. Her educational background includes: PhD from Northeastern University (2010-2013) Degree from University of Rhode Island (2004-2007) Licence from Hacettepe University, Department of Computer Engineering (1991-1998) Dr. Yılmazer Metin's research interests center around GPU architecture and parallel computing systems. Her work addresses critical challenges in synchronization mechanisms for multi-GPU systems, power and energy measurement of embedded GPUs, and efficient implementations of cryptographic algorithms on specialized hardware. She has developed novel approaches to scope promotion in GPU environments, which significantly reduce communication overhead in multiprocessor systems. Her recent work has expanded into healthcare applications, developing privacy-preserving systems for real-time ECG monitoring and exploring homomorphic encryption techniques for secure computation. Her publication record shows a clear trajectory from fundamental GPU architecture research toward security applications and healthcare technology. Early work focused on GPU synchronization and memory management, while more recent publications demonstrate applications in secure medical systems and homomorphic encryption. This evolution reflects a strategic expansion of her core expertise in computer architecture into security-critical domains where hardware-level optimizations can provide significant advantages. Dr. Yılmazer Metin has served as Principal Investigator on multiple research projects: "Time-Critical Job Management in Multi-CPU + Multi-GPU Distributed Heterogeneous Systems" (2018-2019) "A Single-Processor GPU Architecture for More Efficient Graph Algorithms" (2018-2021) "Programmable Synchronization Architecture" (2018-2022) Her laboratory work focuses on GPU architecture and hardware security, with particular emphasis on developing efficient implementations of cryptographic algorithms on GPU platforms and optimizing graph neural network inference on heterogeneous computing systems.

• GPU Computing
• Parallel Processing
• Computer Architecture
• +۵ مورد دیگر