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Selda GüneyView profile

Assistant Professor

• Machine Learning
• Signal Processing
• Image Processing
• +3 more

Selda Güney is an Assistant Professor in the Department of Electrical and Electronics Engineering at Başkent University's Faculty of Engineering. She holds a PhD (2013), Master's (2007), and Bachelor's (2004) in Electrical-Electronics Engineering from Karadeniz Technical University. Her professional experience includes roles as an R&D Engineer at DEKA Digital (2004-2005), Research Assistant at Karadeniz Technical University (2005-2013), and Assistant Professor at Başkent University (2013-present). Her research spans: Machine Learning : Applications in medical imaging, radar, and industrial systems Signal/Image Processing : Focus on real-time classification and fault detection Pattern Recognition : Electronic nose systems and biometric analysis Her recent publications demonstrate strong emphasis on deep learning applications in healthcare (chest X-ray classification, fracture detection) and industrial automation (real-time fault detection systems). Over 70% of her last 15 articles involve medical/industrial AI implementations using convolutional networks. Awards & Honors: TÜBİTAK Domestic PhD Scholarship IBEC ERASMUS Scholarship Research Leadership: Supervised 20+ graduate theses (e.g., radar data classification, medical image steganography) and led 9 R&D projects including: AI-based pathology classification in lung X-rays VR glove development Smart parking systems She is a member of IEEE and ISOCS, and teaches courses including Pattern Recognition, Signals and Systems.

Mahmut AykaçView profile

Assistant Professor

• Electrical and Electronics Engineering
• Communication Engineering
• Image Processing
• +3 more

Assistant Professor Mahmut Aykaç is affiliated with Gaziantep University, Faculty of Engineering, Department of Electrical and Electronics Engineering. He holds a Doctorate (2010-2018), Master's (2006-2009), and Licence (2001-2006) in Electrical and Electronics Engineering from Gaziantep University, specializing in Circuits and Systems Theory. His research spans Image Processing , Machine Learning , and Wireless Communication Systems , with a focus on RFID localization ZigBee-based navigation Chaos theory in cryptography Edge computing for neural networks Legacy textile system modernization Scientific contributions include 7 refereed journal articles and participation in 7 international conferences. Notable projects: ZigBee Campus Navigation System (2013-2017) Jacquard Loom Control System Modernization (2007-2009) Supervised master's theses on: Single-band GSM RF energy harvesting Automatic power factor correction systems Received certification as expert witness in Expropriation and Electrical Engineering fields.

• Image Processing
• Artificial Intelligence
• Machine Learning
• +6 more

Doç. Dr. Emre Sümer, currently serving as an Associate Professor at the Department of Computer Engineering within Baskent University , focuses on image processing, deep learning, and their applications in medical diagnostics and computer vision. His work bridges artificial intelligence with healthcare and geographic information systems. PhD (2011) : Geodesy and Geographic Information Technologies, Middle East Technical University MS (2004) : Geodesy and Geographic Information Technologies, Middle East Technical University BS (2001) : Computer Engineering, Baskent University His research spans medical imaging (e.g., Parkinson's and Alzheimer's detection), steganography for secure data transmission, and machine learning applications in healthcare and urban planning. Recent publications highlight CNN-based diagnostics, sign language recognition, and innovative advertising systems. Scientific awards include the First Oral Presentation Award at the International Congress on Artificial Intelligence in Health (2020). He has supervised multiple PhD/MSc theses on topics like zero-shot sign language recognition and steganography methods. Email: esumer@baskent.edu.tr

• 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.

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.

• Applied Mathematics
• Fractional Calculus
• Special Functions
• +4 more

İsmail Onur KIYMAZ is a Professor at the Faculty of Arts and Sciences, Kırşehir Ahi Evran University , Turkey. His academic journey includes a PhD in Mathematics from Gazi University (2003) and an MSc from Hacettepe University (1997). Research Interests: Applied Mathematics, Fractional Calculus, Special Functions, Differential Equations, Integral Transforms, Numerical Analysis. Students: Supervised 11 theses, including Enes Ata (PhD, 2024), Fatma Karaca Vural (PhD, 2022), and Gizem Tümer (MSc, 2022). Projects: Led 23 projects, such as generalized fractional operators and image encryption algorithms. Collaborated on SEIR epidemic models for vaccine impact analysis. Awards: Recipient of TÜBİTAK UBYT Awards (2013, 2006, 2005, 2003, 2001) and Gazi University Publication Incentive Awards (2005, 2003, 2001). Publications: 40+ articles, focusing on fractional differential equations, generalized special functions, and computational methods.

• Software-Defined Networking (SDN)
• Dynamic Adaptive Streaming over HTTP (DASH)
• Machine Learning
• +3 more

Cihat Cetinkaya is a Professor in the Department of Software Engineering at Mugla Sitki Kocman University. He holds a PhD in Information Technologies from Ege University and has supervised research on deep learning applications in medical imaging and network optimization for video streaming. Bachelor's: Pamukkale University - Computer Engineering Master's: Ege University - Information Technologies Doctorate: Ege University - Information Technologies His research focuses on Software-Defined Networking (SDN) , Dynamic Adaptive Streaming over HTTP (DASH) , and Machine Learning applications in network management and medical imaging. He has pioneered SDN-based architectures for secure IoT systems and optimized DASH streaming via dynamic routing and MPTCP integration. Key trends in his publications include blockchain network optimization , SDN-driven quality of service (QoS) , and deep learning for radiograph analysis . He has developed tools like NetSim for network simulation and contributed to 5G UPF design via XDP programming. Scientific Awards: Distinguished Paper Award (2017) Student Travel Grant Award (2016) Best Paper Award (2014) As Head of the Department of Software Engineering since 2021, he has taught courses in Software Ethics , Software Testing , and Software-defined Networking . He serves on academic incentive committees and international project evaluation panels.

Muhammed Fatih ADAKView profile

Associate Professor

• Computer Software
• Data Mining
• Artificial Learning
• +7 more

Muhammed Fatih ADAK is an Associate Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Computer Engineering. His work spans software engineering, artificial intelligence, and sensor systems with applications in energy, healthcare, and industrial automation. Doctorate: Sakarya University (2016) - Electronic Nose Data Classification with AI Master's: Kocaeli University (2012) - Elevator Simulator Design Bachelor's: Dokuz Eylul University (2009) - Computer Engineering Research focuses on machine learning , software testing , fuzzy logic , anomaly detection , and decision support systems . His articles (2013-2024) explore AI-driven solutions for natural gas monitoring, medical diagnostics, and industrial processes. Recent publications include systematic reviews of AI integration in software engineering phases and predictive models for gas consumption and voice pathology. He supervises graduate students and contributes to academic projects like Smart Gas Sensor Systems and Adaptive Online English Placement Exams . Teaches courses: Data Structures, Fuzzy Logic, Software Testing, Java Programming Co-authored books: Principles of Programming Languages , Visual Programming Managed EU-funded projects like HOPE (street rehabilitation) and AI-Enhanced Performance Evaluation Platforms Develops applications for visually impaired education and workplace safety systems

SEMA KAYHANView profile

Professor

• Image Processing
• Compressive Sensing
• Signal Processing
• +11 more

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.

• Blockchain Technology
• Cyber Security
• Computer Networks
• +6 more

Enis Karaarslan is a Professor in the Department of Computer Engineering at Muğla Sıtkı Koçman University's Faculty of Engineering. With a distinguished academic career spanning over two decades, he has established himself as a leading expert in blockchain technology, cybersecurity, and decentralized systems. His educational background includes a Bachelor's, Master's, and Doctorate all from Ege University, completed between 1994 and 2008. Dr. Karaarslan's research interests focus on the intersection of emerging technologies and practical applications, particularly in blockchain for disaster management, cybersecurity systems, metaverse technologies, and AI applications. His work demonstrates a consistent pattern of addressing real-world challenges through technological innovation, with a strong emphasis on privacy preservation and decentralized architectures. Analysis of his publication record reveals a significant trend toward blockchain applications across various domains including disaster response, healthcare, voting systems, and identity management. His recent work shows increasing focus on metaverse technologies and digital twin applications, reflecting his ability to stay at the forefront of emerging technological paradigms. The breadth of his research spans from theoretical foundations to practical implementations, with numerous papers addressing performance metrics, security evaluations, and real-world case studies. Best Paper Award (2016) Multiple TÜBİTAK research projects as principal investigator or consultant Extensive editorial work for journals including Journal of Metaverse As an educator, Dr. Karaarslan has supervised numerous graduate students through their thesis work and teaches advanced courses in computer networks, decentralized systems, and cybersecurity. His research projects demonstrate strong industry and government collaboration, particularly with TÜBİTAK-funded initiatives addressing national security, privacy concerns, and technological infrastructure development. His laboratory work focuses on practical implementations of theoretical concepts, with emphasis on testbed development for blockchain applications and security evaluation frameworks.

• Computer Engineering
• Multimedia Security
• Embedded Systems
• +4 more

Cem Taşkın is an Assistant Professor at the Department of Computer Engineering, Trakya University, and has served as Department Head since January 2023. Previously, he was Assistant Professor at Tunca Vocational School (2011-2014) and held administrative roles as School Director (2013-2017) and Deputy Director (2012-2013). He earned his PhD in Computer Engineering from Trakya University in 2010. High School: Kırklareli Anatolian High School (1999) Bachelor's: Trakya University, Computer Engineering (2003) Master's: Trakya University, Computer Engineering (2006) PhD: Trakya University, Computer Engineering (2010) His research focuses on Computer Engineering , Multimedia Security , and Embedded Systems , with a strong emphasis on encryption techniques for MPEG video streams and mobile/web application development. Recent work includes applying interactive mobile applications for pediatric chemotherapy treatment (2022) and optimizing embedded systems as dashboards (2016). Publication trends reveal expertise in video encryption (I-frames, byte alignment, XOR operations), chaotic algorithms for sound data security, and software development for educational and administrative systems. His work bridges theoretical cryptography with practical implementations in multimedia and embedded environments. Supervised Master's Theses: Altuğ Yiğit - Human Insight in Business Processes with Deep Learning Temel Yavuz - Corporate Content-Information Management Systems Murat Emre Yücel - Text Classification with Active Learning Projects: Led initiatives at Trakya University on mobile application development laboratories (2016), campus automation systems (2016), and MPEG audio querying (2008). Participated in KOSGEB's R&D Innovation Project for Dream Cash Register/Barkot Systems (2012).

• Computer Science
• Artificial Intelligence
• Algorithms
• +4 more

F. Yeşim İKİKAT serves as a Researcher at the Department of Computer Engineering within the Faculty of Engineering at Turkish-German University, a position held since 2022. Her academic foundation spans computational engineering with interdisciplinary applications in security systems and semantic analysis. Her educational qualifications include: Doctorate in Computer Engineering from Istanbul Technical University Institute of Graduate Education (2019) Master's in Computer Engineering from Yildiz Technical University Institute of Science (2014-2019, with thesis) Bachelor's in Computer Engineering from Atilim University Faculty of Engineering (2007-2012) Research interests center on Artificial Intelligence, Algorithms and Computational Theory, and Information Security and Cryptology, with specialized work in Parallel Algorithms, Natural Language Processing, and Image Encryption. Her methodology combines computational modeling with cryptographic techniques to solve complex engineering and information system challenges, particularly in high-performance computing environments and secure data transformation. Publication trends reveal evolving expertise from computational mechanics (2012 thermoelasticity simulations) to security applications (2018 image encryption) and semantic analysis (2015 Wikipedia linking). This progression demonstrates consistent application of algorithmic innovation across engineering simulations, multimedia security, and knowledge representation domains. No scientific awards were documented in the source material. Advising activities and research grants are not referenced in the available information. Laboratory affiliations or research team memberships were not specified in the provided text.

Tolga AyavView profile

Professor

• Formal Methods for Software Testing
• Hardware Component and On-Chip System Tests
• Real-Time and Fault-Tolerant Embedded Systems
• +5 more

Professor Tolga Ayav is affiliated with the Department of Computer Engineering at Izmir Institute of Technology , where he has served as faculty since 2006. He received his BSc in Electrical and Electronics Engineering (1995) from Dokuz Eylül University, MSc in Computer Engineering (1999) from Izmir Institute of Technology, and PhD in Computer Engineering (2004) from Ege University. He was a researcher at INRIA Rhone-Alpes in 2005. Education BSc: Electrical and Electronics Engineering, Dokuz Eylül University (1995) MSc: Computer Engineering, Izmir Institute of Technology (1999) PhD: Computer Engineering, Ege University (2004) Research Interests include formal methods for software testing, hardware component and on-chip system tests, real-time and fault-tolerant embedded systems, blockchain applications, and machine learning. His work focuses on: Formal verification techniques Real-time system optimization Hardware-software co-design Blockchain-based security solutions Mathematical modeling in testing Recent Publications span topics like: Deep learning for livestock monitoring Blockchain in IoT security Fourier expansion in fault analysis Optimized data replication strategies Finite state machine testing Scientific Awards include: Best Paper Award at IEEE CBDCom 2016 for cloud data replication research Teaching includes courses such as: CENG 312: Computer Networks CENG 523: Advanced Topics in Real-Time Systems CENG 215: Circuits and Electronics Projects he has led include: TÜBİTAK TEYDEB: Spectrally Efficient Small Cell Base Station Design BAP: Dedicated Server for Physical Network Applications Lab Leadership : He leads the DCS Research Group at Izmir Institute of Technology, focusing on distributed computing and real-time systems.

• Adaptive Video Streaming
• Internet Performance Measurements
• Peer-to-Peer (P2P) Networks
• +3 more

Turhan Tunalı is a distinguished Professor in the Department of Computer Engineering at Izmir University of Economics . He holds a BSc in Electrical Engineering from Middle East Technical University (1978), an MSc in Applied Statistics from Ege University (1980), and a DSc in Systems Science and Mathematics from Washington University in St. Louis (1985). Current Professor at Izmir University of Economics (since 2009) Director, Ege University International Computer Institute (2001–2009) Dean, Izmir University of Economics (2010–2014) Visiting Professor at Loyola University Chicago (2000–2001) His research focuses on adaptive video streaming and Internet performance measurements , with publications spanning P2P networks, WDM optical networks, and scalable video encryption. Recent work includes comparative studies on MLR routing, shared backup strategies, and hierarchical clustering frameworks for streaming systems. Key article trends reveal expertise in network resilience , adaptive algorithms , and optical communication design . He has collaborated extensively with researchers like Muge Sayit, Gül Boztok Algın, and Sercan Demirci on these topics. As an active academic leader, he has directed research institutes and served as department head, contributing to the advancement of computer engineering through both theoretical and applied research.