Find Academic Supervisors

• Computer Architecture
• Reliable Computer Design
• Fault Detection and Recovery
• +3 more

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)

• High-Energy Physics
• Particle Physics
• Proton-Proton Collisions
• +5 more

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.

İBRAHİM RIZA HALLAÇView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Parallel and Distributed Systems
• +3 more

İbrahim Rıza Hallaç is an Assistant Professor at RAFET KAYIŞ FACULTY OF ENGINEERING, Department of Computer Engineering. He holds a PhD (2021), Master's (2014), and Bachelor's (2011) in Computer Engineering from Firat University, with doctoral research on social media analysis using deep learning methods under advisor Galip Aydın. His research focuses on: Artificial Intelligence and language models Machine learning for distributed systems Big data analytics and cloud computing Natural language processing applications Social media sentiment analysis Radar-based object detection systems His publications (2015-2024) demonstrate consistent focus on machine learning applications across diverse domains including social network analysis, distributed computing, Turkish NLP, and sensor data processing. Recent works emphasize radar-based multi-target detection (2024), credit scoring models (2023), and wind speed estimation (2023), reflecting expertise in scaling AI solutions for real-world problems. He has led four national R&D projects: Deep Learning-Based Face Recognition Authorization System (2017-2019) DEĞİRMEN Big Data Analysis Platform for Turkish Armed Forces (2017-2021) KOSGEB Innovation Program for Face Recognition Systems (2017-2019) Cloud-Based Social Media Reputation Analysis System (2015-2017) No students, awards, or contact emails are documented in available records.

• Electromagnetic Theory
• Inverse Scattering Problems
• Computational Electromagnetics
• +3 more

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 .

• Machine Learning
• Field-Programmable Gate Arrays (FPGA)
• Network Traffic Classification
• +5 more

Prof. Dr. Oğuzhan ERDEM is a faculty member at Trakya University Faculty of Engineering , Department of Electrical and Electronics Engineering since 2023. He earned his PhD in Electrical and Electronics Engineering from Middle East Technical University in 2011 and served at various academic roles across 22 years, including Department Head since 2021. PhD: Middle East Technical University (2011) Visiting Scholar: University of Southern California (2010-2011) His research focuses on machine learning applications in biomedical diagnostics and FPGA-based network processing . Recent publications explore Parkinson's disease detection through keystroke analysis, cough sound diagnostics, and hardware-accelerated network traffic classification. Key article trends show: 2023-2025: Deep learning for medical diagnostics 2016-2020: Hardware-optimized network processing 2010-2015: FPGA-based IP lookup architectures Awards: Middle East Technical University 2011 Doctoral Thesis of the Year He has supervised 6 graduate theses and led 2 major projects including Early Detection of Parkinson's Disease Using Multimodal Signals (2021). Patent co-inventor in systolic array architectures.

• Parallel Computing
• Algorithm Design
• Computer Architecture
• +5 more

Prof. Haluk Rahmi Topcuoğlu is a Full Professor at the Department of Computer Engineering, Faculty of Engineering, Marmara University since 1999. His research focuses on parallel algorithm design, multicore computing, evolutionary algorithms, and dynamic optimization problems. He holds a PhD in Computer Science from Syracuse University (1999), an M.S. from Boğaziçi University (1991), and a B.S. from Boğaziçi University (1993). Research Highlights: Recipient of IBM Faculty Award (2008) Best Paper Award at IEEE ISDA (2010) Marmara University Publication Impact Award (2012) Professional Roles: Editorial Board Member - Cluster Computing Journal (SCI-Expanded) Reviewer for IEEE TPDS, JPDC, IEEE TEC, and conferences like IPDPS/HPDC

• Computational Electromagnetics
• MATLAB Applications for Engineering
• Applied Mathematics
• +7 more

Prof. Dr. Gökhan Apaydin is a full Professor at the Department of Electrical and Electronics Engineering, Faculty of Engineering and Natural Sciences, Uskudar University. He holds a PhD from Bogazici University (2007) and has held academic positions at institutions including the University of Technology Zurich and a visiting role at the University of Illinois at Urbana-Champaign. His research focuses on computational electromagnetics, radio wave propagation, and numerical modeling techniques. Education: BSc (2001), MSc (2003), PhD (2007) in Electrical and Electronics Engineering from Bogazici University Research Interests: Electromagnetic diffraction modeling, MATLAB-based simulations, numerical methods (FDTD, MoM), surface wave propagation, and renewable energy systems. His work emphasizes practical applications in radio wave modeling and environmental impact assessments. Publications: His articles focus on diffraction phenomena, waveguide analysis, and tool development (e.g., PETOOL). Recent trends include hybrid numerical methods and real-world terrain modeling for radiowave prediction. Awards: Received TÜBİTAK Publication Incentive Awards (2021). Administration & Leadership: Serves as Deputy Head of the Electrical Engineering Department, chairs international committees (URSI), and oversees projects like the Electromagnetic Wave Propagation Package. Active in academic governance and Bologna Process coordination. Labs/Teams: Leads the Electromagnetic Research Group, focusing on wave propagation and measurement validation.

• Artificial Intelligence
• Neural Networks
• Robotics
• +5 more

Abdullatif Baba is an Assistant Professor in the Department of Computer Engineering at Turkish Aeronautical Association University. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and sustainable energy systems. He develops solutions for smart infrastructure, including AI-driven energy forecasting, autonomous drones for grid maintenance, and hyperspectral imaging techniques. His research interests span: AI/ML Systems : Neural networks, probabilistic forecasting, and FPGA-accelerated deep learning Robotics : Autonomous drones with computer vision for industrial and energy applications Sustainable Energy : Solar-based systems, smart grid optimization, and consumption prediction Security : Chaos-based cryptographic systems for secure communications Recent publications (2020-2024) demonstrate strong trends in practical AI implementations. Key themes include energy forecasting using adaptive neural networks (11 papers), robotics for infrastructure maintenance (4 papers), computer vision for biometrics and imaging (3 papers), and cryptographic systems (2 papers). Methodologies frequently involve hybrid approaches combining ANN, fuzzy logic, and hardware acceleration. No awards, students, or grant details were mentioned in the source material. Research collaborations include institutions in Turkey and the Middle East.

Ali KarakuşView profile

Associate Professor

• Computational Fluid Dynamics
• High-Order Finite Element Methods
• Multiphase Flows
• +5 more

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.

Ertuğrul TAÇGINView profile

Professor

• Occupational Safety
• Robotics
• Artificial Intelligence
• +5 more

Prof. Dr. Ertuğrul TAÇGIN serves as Head of the Department of Mechanical Engineering at Doğuş University's Faculty of Engineering. With a career spanning over three decades, he has contributed to robotics, occupational safety, and sustainable manufacturing through extensive research and publications. His research interests focus on: Occupational Safety and Risk Analysis Expert Systems for Robotics and Manufacturing Biomedical Signal Processing for Brain-Computer Interfaces Sustainable Development in Industrial Production Recent publications demonstrate expertise in CNN models for EEG classification, QFD methodology for orthotic devices, and intelligent systems for accident causation analysis. Collaborative work with researchers like Emre ARI and Ayşenur ERDİL highlights interdisciplinary applications of AI and engineering principles. As an advisor, he has supervised publications in journals such as: Biomedical Signal Processing and Control Global Journal of Business and Economics Journal of Intelligent Manufacturing His work bridges robotics, safety engineering, and sustainable design across multiple industries including healthcare, textiles, and construction.

Mustak E. YalcinView profile

Professor

• Nonlinear Dynamics
• Cryptography
• Cellular Neural Networks
• +3 more

Mustak E. Yalcin is a Professor in the Department of Electronics and Telecommunications Engineering at Istanbul Technical University (ITU). He holds a PhD from Katholieke Universiteit Leuven (2004), an MSc from ITU (1997), and a BSc from ITU (1993). His research focuses on nonlinear dynamics, chaos theory, FPGA-based systems, and secure communication. He has been elevated to IEEE Senior Member (2019) and serves as an Associate Editor for multiple journals, including the International Journal of Bifurcation and Chaos and SpringerBriefs in Nonlinear Circuits. His work spans applications in cryptographic systems, cellular neural networks, and hardware security. Notable contributions include FPGA implementations of hyperchaotic systems for medical image encryption, and designs for GPS spoofing detection. He leads projects on sensor-based navigation systems, smart weighing technologies, and energy-efficient embedded systems. Recent activities include chairing tracks at IEEE conferences and organizing events like FOSSistanbul. His lab actively explores wave computing, memristor-based networks, and bio-inspired algorithms for odor classification. Current projects include the design of fault-tolerant cryptographic hardware and real-time spectrum analyzers.

• Parallel and Distributed Systems
• Cloud Computing
• Computer and Communication Networks
• +12 more

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.

• Cyber-Physical Systems
• Distributed Systems
• Embedded Systems
• +3 more

Brian Nielsen is an Associate Professor at the Department of Computer Science, Aalborg University, under the Technical Faculty of IT and Design. His research focuses on Cyber-Physical Systems, Distributed Systems, and Intelligent Systems, with a particular emphasis on energy-efficient design and distributed reachability analysis. Research Interests: Cyber-Physical Systems, Distributed Systems, Embedded Systems, Intelligent Systems, Model-Based Design, Optimization Supervision: Supervised PhD theses on topics related to energy efficiency (2024) and time/cost optimization (2016) Contact: bnielsen@cs.aau.dk | Personal Website

• Biomedical Engineering
• Biomedical Image Processing
• Medical Physics
• +5 more

Dr. PELİN ÇİRİŞ is an Assistant Professor in the Department of Biomedical Engineering at the Faculty of Engineering, Akdeniz University, Antalya, Turkey. She also serves as the Director of the Biomedical Technologies Application and Research Center and Deputy Director of the Science and Technology Application and Research Center at Akdeniz University. Previously, she served as Head of Department for Biomedical Engineering from 2014-2020 and continues as Deputy Head since 2016. Her academic career includes significant postdoctoral training at Harvard Medical School and Yale University. Education: Post Doctorate, Harvard University, Harvard Medical School, Brigham And Women's Hospital, Radiology (2013-2015) Post Doctorate, Yale University, School Of Medicine, Diagnostic Radiology (2012-2013) Doctorate, Yale University, School Of Engineering And Applied Science, Biomedical Engineering (2008-2012) Masters (Non-Thesis), Yale University, School Of Engineering & Applied Science, Engineering And Applied Science (2008-2010) Postgraduate, Johns Hopkins University, School Of Engineering, Biomedical Engineering (1998-2000) Undergraduate, Purdue University, School Of Electrical And Computer Engineering, Electrical Engineering (1994-1998) Dr. Çiriş's research spans multiple domains of biomedical imaging and engineering, with a strong focus on magnetic resonance imaging (MRI) techniques and applications. Her work encompasses advanced MRI physics, quantitative imaging methods, and clinical applications across various medical fields. She has made significant contributions to signal modeling in MRI, particularly in cancer imaging contexts including prostate and cervical cancers. Her research also extends to neuroimaging for brain tumor visualization and white matter tractography, as well as cardiac imaging applications for tissue characterization and functional assessment. She has developed innovative approaches like the GAME (Gaussian Augmentation of the Monoexponential) model for analyzing MRI signal decays in cancer tissues. The trajectory of Dr. Çiriş's publication record reveals a progression from fundamental MRI techniques to sophisticated clinical applications. Her early work focused on image reconstruction, parallel imaging, and real-time interventional guidance. Over time, her research evolved to emphasize quantitative approaches for tissue characterization in oncology, particularly in gynecologic and prostate cancers. Recent publications demonstrate expertise in advanced modeling techniques for MRI signal decays, thermometry applications, and image processing methods for clinical decision support. This progression reflects a career dedicated to bridging engineering innovation with practical clinical applications across multiple medical specialties. Scientific Awards: Magna Cum Laude Award (Gynecological cancers), International Society for Magnetic Resonance in Medicine (2015) Magna Cum Laude Award (Prostate cancer), International Society for Magnetic Resonance in Medicine (2015) PhD Candidacy Awarded With Distinction, Yale University (2012) Travel Grant for Top 25 Papers, IEEE International Symposium on Biomedical Imaging (2007) Melvin Judkins Young Investigator Award, American Heart Association (2007) Academic Honors and Dean's Lists, Purdue University (1998) Dr. Çiriş has secured research funding including the project 'Assessing validity of MRI T2* hypoxia measurement in cervical cancer' (2014-2015). She serves as an Editor for the Journal of Magnetic Resonance Imaging since 2015, demonstrating her standing in the MRI research community. She has contributed to academic governance as a jury member for Assistant Professorship Appointment Committee at Akdeniz University. Her leadership extends to directing research centers focused on biomedical technologies at Akdeniz University, where she oversees interdisciplinary teams working on medical imaging technologies. As Director of the Biomedical Technologies Application and Research Center and Deputy Director of the Science and Technology Application and Research Center, Dr. Çiriş leads interdisciplinary teams focused on advancing medical imaging technologies and their clinical translation. Her centers foster collaboration between engineers, physicists, clinicians, and computer scientists to develop innovative solutions for diagnostic and therapeutic challenges in medicine, particularly in the areas of cancer imaging, neuroimaging, and cardiac applications.

• Computer Sciences
• Computer Graphics
• Engineering and Technology
• +3 more

ÖMER ÇAKIR is a Lecturer at the College of Engineering , Karadeniz Technical University , Department of Computer Engineering. His work spans computer graphics, software engineering, and signal processing. Education: Undergraduate (2001) and Postgraduate (2004) in Computer Engineering at Karadeniz Technical University. Academic Positions: Lecturer (2002–Present), Research Assistant (2001–2002). Research focuses on Computer Graphics , Signal Processing , and Optimization Algorithms . His conference papers address topics like virtual surgery simulations , fractured object reassembly , and TDOA-based localization . Key publication trends include parallel computing , 3D reconstruction , and PSO optimization . He has contributed to 13 peer-reviewed conferences. His contact email is cakiro@ktu.edu.tr , and he teaches BİLGİSAYAR GRAFİKLERİ-I and DATA STRUCTURES .