جست‌وجوی استاد و پژوهشگر

Müştak Erhan Yalçınمشاهده پروفایل

استاد

• Nonlinear Circuits and Systems
• Chaos Theory
• Cellular Neural Networks
• +۳ مورد دیگر

Prof. Müştak Erhan Yalçın is a Professor of Electronics and Telecommunications Engineering at Istanbul Technical University (ITU). He holds a Ph.D. from Katholieke Universiteit Leuven (2004) and degrees from ITU (1997, 1993). His research focuses on nonlinear circuits, chaos theory, cellular neural networks, and embedded systems. He has authored numerous publications in top-tier journals and conferences, with recent work emphasizing secure communication, GPS spoofing detection, and chaotic systems applications. He actively contributes to the academic community through editorial roles (e.g., Associate Editor of IEEE Transactions on Circuits and Systems-II) and organizing international conferences. Notable recognitions include elevation to IEEE Senior Member (2019) and inclusion in ITU's Career-Long Impact category (2024). Education: Ph.D. in Electronics Engineering, Katholieke Universiteit Leuven, 2004 M.Sc., Istanbul Technical University, 1997 B.Sc., Istanbul Technical University, 1993 Research Interests: Nonlinear Circuits and Chaos Theory Cellular Neural Networks and Wave Computing Embedded Systems and Hardware Security Chaotic Signal Processing and Cryptography Recent Projects: TÜBİTAK-funded project on active shield design (2021) Development of GPS spoofing detection methods (2024) Secure communication systems using chaotic oscillators Grants & Awards: IEEE Senior Member (2019) Associate Editor, IEEE Transactions on Circuits and Systems-II (2020–2021) Recipient of TÜBİTAK 1505 Collaboration Program (2021) Labs & Teams: Leading research on nonlinear systems and embedded security within ITU's Electronics and Telecommunications Engineering Department, collaborating with industry partners like Aselsan.

Ersan Yazanمشاهده پروفایل

استادیار

• Machine Vision
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Ersan Yazan serves as an Assistant Professor in the Department of Computer Engineering at the Faculty of Engineering, Adiyaman University, Turkey. He joined the university in December 2011 as a lecturer at Besni Vocational School and has since advanced through academic ranks, achieving his current position effective February 2025. Educational Background: Doctorate (2016-2024): Inonu University, Faculty of Engineering, Department of Computer Engineering Master's Degree (2013): Firat University, Faculty of Engineering, Department of Computer Engineering Bachelor's Degree (2000-2007): Erciyes University, Faculty of Engineering, Department of Computer Engineering Ersan Yazan's research spans machine vision, machine learning, deep learning, and brain-computer interaction. His work demonstrates significant expertise in optimization algorithms, image processing, and medical applications. Early research focused on stochastic gradient descent techniques and fabric defect detection, while recent publications emphasize medical image analysis, particularly in breast cancer detection and robot-assisted neurosurgery. His research consistently bridges theoretical computer science with practical applications across industrial and medical domains. Yazan's publication history shows a clear progression from foundational work in computer vision toward specialized medical applications. His most recent work (2024) on frameless registration for robot-assisted brain surgery demonstrates his shift toward cutting-edge medical technology applications. His research integrates computer vision, machine learning, and robotics to solve complex problems in both industrial quality control and medical diagnostics. As an educator, Yazan has taught numerous courses including System Analysis and Design, Web Design Fundamentals, Visual Programming, Network Fundamentals, and Microcontroller Applications across both associate and bachelor's degree programs. He previously served as Department Head from 2012 to 2018, demonstrating leadership within the academic structure.

Murat SARANمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Gamification
• Intelligent Learning Systems
• +۵ مورد دیگر

Dr. Murat SARAN is an Assistant Professor in the Department of Computer Engineering at Çankaya University, Ankara, Turkey. He serves as Director of the Distance Education Application and Research Center (DEARC), focusing on innovative educational technologies. His academic background includes a PhD (2009) and MSc (2003) in Computer and Educational Technologies from Middle East Technical University (1999-2009). Education: Bachelor's: Middle East Technical University, Computer and Educational Technologies (1999) Master's: Middle East Technical University, Computer and Educational Technologies (2003) PhD: Middle East Technical University, Computer and Educational Technologies (2009) Research Interests: Dr. SARAN specializes in Human-Computer Interaction, Gamification, and Mobile Learning. His work spans algorithmic thinking, context-aware systems, virtual reality integration in education, and data augmentation techniques for machine learning. He has contributed to projects addressing digital literacy in primary education and emotion recognition via computer vision. Key Projects: ICOINS (2018–2020): Developed Industry 4.0 training tools for SMEs (€203,858) Mesh-Based Mobile Education Platform (2012–2014): Managed a TL 373,128 project for SME/educational institutions HESAPRO (2011–2013): Analyzed health-safety-productivity links in workplaces (€103,000) Grants & Labs: His research has been supported by TÜBİTAK and EU grants. He leads the DEARC lab, focusing on distance education innovation and mobile learning systems.

• Internet of Things (IoT)
• Embedded Systems
• Precision Agriculture
• +۳ مورد دیگر

Deniz Taşkın is an Associate Professor at the Department of Computer Engineering , Trakya University , Turkey. He has served in various academic and administrative roles since 2002, including Head of Department of Information Technology (since 2024) and Deputy Head of Department (since 2016). Education: PhD in Computer Engineering (2007) Master's in Computer Engineering (2004) BSc in Computer Engineering (2002) Edirne Science High School (1998) Research Interests: His research focuses on Internet of Things (IoT) , Embedded Systems , and Precision Agriculture , with applications in sensor networks, wireless communication, and agricultural monitoring. He explores 3D Modeling techniques for optical systems and contributes to Cybersecurity in multimedia and IoT environments. Publication Trends: Deniz has published 15+ articles on IoT architectures, Bluetooth Low Energy sensor networks, 3D calibration methods, and video encryption. His work bridges Digital Circuit Design with Agricultural Technology , emphasizing energy efficiency and real-time data processing. Scientific Awards: 2017 Trakya Project Market: Electric Motor Driver for Autonomous Vehicles 2016 TÜBİTAK: Electromobile Category Runner-Up and Promotion Award 2015 TÜBİTAK: Solar-Powered Vehicle Design Award 2015 Edirne Governorship: Provincial Achievement Certificate Advising and Grants: He has supervised 5 PhD theses and 7 Master's theses , including projects on IoT in Precision Agriculture and FPGA Circuit Design . As a principal investigator, he led 8 scientific projects funded by Trakya University and KOSGEB, focusing on embedded systems, data security, and smart automation. Labs and Teams: He contributes to IoT Research and Embedded Systems Development at Trakya University, collaborating with multidisciplinary teams in agricultural technology and digital design. His work includes designing self-powered sensor nodes and FPGA-based hardware.

Ege KIPMANمشاهده پروفایل

استادیار

• Computer Science
• Data Mining
• Machine Learning
• +۴ مورد دیگر

Ege KIPMAN is an Assistant Professor in the Department of Computer Engineering at Istanbul Beykent University's Faculty of Engineering and Architecture. He has held academic roles since 1999, including Lecturer and Research Assistant positions, and currently serves as Deputy Director of Research and Application Center since 2021. Research Focus: Machine learning applications, semantic technologies, computer networks (IPv6), and e-commerce systems. Key Contributions: Developed a mobile payment wallet architecture, explored data mining in travel agencies, and created a hybrid system for e-commerce. Theses Supervised: Advised 5 students (2016-2023) on topics ranging from student performance prediction to facial recognition algorithms. Administrative Roles: Deputy Director of Research and Application Center (2021-present).

• Information Security
• Cryptology
• Embedded Systems
• +۵ مورد دیگر

Prof. Dr. Sıddıka Berna Örs Yalçın is a Professor at Istanbul Technical University , Faculty of Electrical and Electronics Engineering, Department of Electronics and Communication Engineering since 2020. She holds a PhD from Katholieke Universiteit Leuven (1999) and has maintained continuous academic engagement in cryptology, embedded systems, and hardware security. Education: PhD in Electrical Engineering, Katholieke Universiteit Leuven (1999) Master's in Electronics and Communications Engineering, Istanbul Technical University (1995) Licence in Electronics and Communication Engineering, Istanbul Technical University (1995) Her research focuses on post-quantum cryptography , side-channel attack mitigation , and hardware implementation for security systems. Recent work includes FPGA-based AI accelerators, IoT power consumption modeling, and quantum-resistant cryptographic algorithms. Current projects center on RISC-V processor optimization, embedded security, and hardware implementations for 5G communications. Her Scopus h-index is 17 with over 1353 citations, reflecting her impact in computer hardware and cryptographic engineering domains. Notable Research Outputs: Quantum tent map-based S-box designs for image encryption (2024) Post-quantum modular multiplication algorithms (2024) RISC-V implementation of CRYSTALS-Kyber (2023) IOT power consumption estimation frameworks (2024)

ABDULLAH GÖKYILDIRIMمشاهده پروفایل

دانشیار

• Chaotic Systems
• Fractional-Order Dynamics
• Memristive Circuits
• +۴ مورد دیگر

ABDULLAH GÖKYILDIRIM is an Associate Professor at the Department of Electromagnetic Fields and Microwave Technology within the Faculty of Engineering and Natural Sciences at Bandırma Onyedi Eylül University. He has held this position since 2024, following prior roles as Doctor Lecturer at Bingöl University (2011–2019). His research focuses on chaotic systems, fractional-order dynamics, memristive circuits, and secure communication, with applications in electronic circuit design and control systems. Key research areas include: Fractional-order chaotic systems and their applications in encryption and energy systems Memristive circuit design and nonlinear control techniques Chaotic synchronization and secure communication protocols Electronic implementations of chaotic systems using standard components His recent work emphasizes the practical realization of theoretical models through microcontroller-based implementations and sliding mode control. Statistical contributions include 21 articles (5% of the Electrical and Electronics Engineering Department's total) and 13 conference contributions (5% of departmental output). Student advising hours are held on Thursdays from 15:15 to 17:00. No scientific awards are explicitly listed in the provided data.

• Computer Networks
• Video Streaming
• Multimedia Systems
• +۴ مورد دیگر

Prof. Turhan TUNALI is a distinguished Professor in the Department of Computer Engineering at Izmir University of Economics' Faculty of Engineering. With a Ph.D. in Nonlinear Control Systems from Washington University in Saint Louis (1985), his academic career spans over three decades since beginning as an Assistant Professor at Ege University in 1986. Ph.D. - Nonlinear Control Systems, Washington University in Saint Louis (1985) M.S. - Applied Statistics, Ege University (1980) B.S. - Electrical Engineering, Middle East Technical University (1978) Professor TUNALI's research focuses primarily on computer networks, with specialized expertise in video streaming systems, optical networks, and intelligent transportation systems. His work bridges theoretical networking principles with practical implementations in multimedia delivery and transportation applications. He has made significant contributions to peer-to-peer video streaming architectures, bandwidth adaptation algorithms, and optical network resilience strategies. His research demonstrates a consistent trajectory from foundational network protocols to advanced multimedia delivery systems. Analysis of his 15 most recent publications reveals a strong concentration in networked multimedia systems, particularly peer-to-peer video streaming technologies and optical network architectures. His work shows evolution from basic streaming protocols to sophisticated hierarchical clustering frameworks, backup strategies for resilient networks, and security implementations for scalable video coding. The publications span high-impact journals including IEEE Access, Signal Processing: Image Communication, and Computer Standards and Interfaces. Professor TUNALI has served as Editor for the Turkish Journal of Electrical Engineering and Computer Sciences (2015-2016) and has contributed to TÜBİTAK projects. His research has been supported by various funding mechanisms, though specific grants are not detailed in the provided information. He has supervised an impressive 20 graduate students to completion, including 11 PhD candidates and 9 master's students, primarily at Ege University. His advisees have pursued research in areas including video streaming, optical networks, intelligent transportation systems, and healthcare information systems, reflecting his broad research influence. Professor TUNALI maintains an active research laboratory focused on networked multimedia systems, with particular emphasis on resilient video delivery architectures and intelligent transportation applications. His current work appears to be investigating advanced optical networking strategies and next-generation video streaming technologies.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Övgü Öztürk Ergün is an Assistant Professor in the Department of Software Engineering at Muğla Sıtkı Koçman University's Faculty of Engineering. She holds a Ph.D. from The University of Tokyo's Department of Frontier Informatics. Her research focuses on computer vision, machine learning, and AI applications in areas such as augmented reality, cultural heritage digitization, and human behavior analysis. She has led multiple TÜBİTAK-funded projects including 'Customer Tracking and Interest Measurement Technologies for Retail Sector Sales Performance Improvement' and '3D Modeling of Cultural Heritage Sites.' Her work spans academic publications, industry collaborations, and innovative teaching in software engineering and interactive multimedia systems. Education: Middle East Technical University, B.Sc. Electrical & Computer Engineering (2003) University of Tokyo, Ph.D. Frontier Informatics (2010) Research Interests: Her interdisciplinary research integrates computer vision with real-world applications, including privacy-preserving biometrics, smart environment monitoring, and cultural heritage preservation. She has pioneered ontology-based systems for Turkish cuisine and developed AR tools for virtual try-on. Her work emphasizes ethical AI and context-aware systems, with recent focus on food recognition using CLIP models and churn prediction in telecom sectors. Awards & Grants: TÜBİTAK Undergraduate Software Projects Competition (2013) Robot Days 3rd Place (2013) Completed TÜBİTAK 1001/1505 projects totaling over 500k USD funding Advising & Labs: Supervised BENGÜ-ÖZTÜRK's thesis on food image recognition. Active in the University's Research & Application Centers for Computer Vision and AR/VR development. Collaborates with ISTKA and Ministry of Development on cultural heritage digitization projects.

• Image Processing
• Biomedical Signal Analysis
• Medical Imaging
• +۳ مورد دیگر

Dr. Gizem DURSUN DEMİR is a Researcher at the Department of Electrical and Electronics Engineering, Faculty of Engineering and Natural Sciences, Suleyman Demirel University. She holds a Ph.D. in Electrical and Electronics Engineering from the same institution (2023). Her research focuses on image and biomedical signal processing, with applications in medical diagnostics and cybersecurity. Education: Bachelor's: Suleyman Demirel University, Electronics and Communication Engineering (2014) Master's: Suleyman Demirel University, Electronics and Communication Engineering (2017) Ph.D.: Suleyman Demirel University, Electronics and Communication Engineering (2023) Research Interests: Image/video processing, biomedical signal analysis, medical imaging, cryptography, machine learning, and neurodegenerative disease diagnostics. She specializes in developing AI-driven tools for automated analysis of biomedical signals and medical imaging. Recent Work Trends: Recent publications emphasize dental radiography segmentation using generative models, automated calcium imaging analysis for neurodegenerative diseases (e.g., ALS), and AI applications in pathology. She also explores secure image encryption techniques. Grants & Projects: EU H2020 Project: Automated Functional Screening of IgGs for Neurodegenerative Disease Diagnostics (2018–2023) National Project: Image Encryption via Lossless Transform Methods (2016–2017) Labs/Teams: Collaborates with teams at the University of Belgrade and Suleyman Demirel University on neuroglial structure analysis and biomedical signal processing.

Ferdi DOĞANمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Ferdi Doğan is an Assistant Professor in the Department of Computer Engineering at Adıyaman University. He holds a PhD in Software Engineering (2021, Fırat University), an MSc in Computer Systems (2012, Sakarya University), and a BSc in Computer Systems (2002, Selçuk University). His research focuses on artificial intelligence, machine learning, deep learning, image processing, and cybersecurity. He has led TÜBİTAK projects on AI-driven solar panel defect detection, SCADA system security, and post-earthquake psychological analysis using AI. He is a member of IEEE and ACM, and has presented at over 10 international conferences. Professional Experience: Joined Adıyaman University as a Lecturer in 2007, became Department Head (2011-2019), and is currently Director of the Research and Application Center. He advises graduate theses and consults on TÜBİTAK projects. His applied research includes AI in agriculture, solar energy, and SCADA security algorithms. Teaching: Courses include Artificial Neural Networks, Internet Programming, and Software Engineering. He has taught at both undergraduate and graduate levels since 2002, with over 50 recorded courses in programming, algorithms, and web design. Awards: No specific awards listed but has secured TÜBİTAK grants and participated in international projects. His work has been cited over 12 times in peer-reviewed journals.

Mustak Erhan Yalcinمشاهده پروفایل

استاد

• Field-Programmable Gate Arrays (FPGA)
• Neural Networks
• Image Encryption
• +۷ مورد دیگر

Mustak Erhan Yalcin is a Professor at Istanbul Technical University within the Department of Electronics and Communication Engineering. His research spans hardware security, chaos theory, and signal processing, with a focus on FPGA-based systems, GPS spoofing detection, and image encryption. Key research areas: FPGA, neural networks, hyperchaotic systems, TRNG, GPS security. Recent publications (2023-2024) address encryption designs, spoofing detection, and radiation-tolerant hardware. Active in project leadership, including FPGA-based communication blocks and GPS security systems. Recipient of the 2016 Graduation Design and Project Awards in Electronics-Communication-Biomedical. Contact: yalcinmust@itu.edu.tr

Fahrettin Horasanمشاهده پروفایل

دانشیار

• Machine Learning
• Data Security
• Recommender Systems
• +۳ مورد دیگر

Dr. Fahrettin Horasan is an Associate Professor in the Department of Computer Engineering at the Faculty of Engineering and Natural Sciences . His research focuses on applied computational methods in data security, machine learning, and information retrieval systems. Specialized in medical image watermarking and encryption using matrix decomposition techniques (SVD, ULV) Developed novel collaborative filtering recommender systems with hybrid approaches and matrix approximation Contributions in sentiment analysis for healthcare and e-commerce domains His recent publications highlight interdisciplinary work combining cryptology, biomedical imaging, and large-scale data processing. Notable methods include chaotic system-based encryption, latent semantic indexing, and gradient boosting for darknet traffic analysis. While specific awards, educational background, and student advisement details are not publicly detailed in the provided texts, his technical output reflects active engagement in computational science advancements.

Ünal ÇAVUŞOĞLUمشاهده پروفایل

دانشیار

• Cybersecurity
• Network Security
• Intrusion Detection Systems
• +۶ مورد دیگر

Prof. Dr. Ünal Çavuşoğlu is an Associate Professor at the Department of Software Engineering, Faculty of Computer and Information Sciences, Sakarya University. With a doctorate in chaos-based encryption algorithms (2016) and a master's degree comparing network simulation tools (2014), his research focuses on cybersecurity, machine learning, and chaos theory. He has contributed extensively to intrusion detection systems, IoT security, and cryptographic protocols. Education: Doctorate (2016), Master's (2014), and Bachelor's (2011) in Computer Engineering. Research Interests: Cybersecurity frameworks, machine learning adaptation for threat detection, chaotic encryption, and IoT communication protocols. Recent Work: 2025 publications on homomorphic encryption and LSTM-based intrusion detection demonstrate cutting-edge applications of deep learning in security domains. His 2019-2024 publications reveal a trajectory from foundational chaos theory to applied IoT and cloud security solutions. Key methodologies include genetic algorithms, fractional calculus, and hybrid encryption systems.