جستجوی استاد راهنمای دانشگاهی

Ali Yaparمشاهده پروفایل

استاد

• Electromagnetics
• Microwave Engineering
• Antenna Technologies
• +۳ مورد دیگر

Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.

Tamer Ölmezمشاهده پروفایل

استاد

• Biomedical Signal Processing
• Brain-Computer Interfaces
• Deep Learning
• +۷ مورد دیگر

Tamer Ölmez is a Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University (ITU), College of Engineering, where he conducts cutting-edge research in biomedical signal processing, brain-computer interfaces (BCI), and deep learning applications in medical systems. His work bridges engineering and neuroscience, with a strong focus on EEG-based motor imagery classification, medical image analysis, and embedded deep learning systems. His research interests include motor imagery EEG signal processing , brain-computer interfaces , feature extraction , deep neural networks , classification algorithms , and medical image analysis . He applies machine learning and signal processing techniques to improve diagnostic accuracy and system performance in neuroengineering and healthcare technologies. The recent publications highlight a consistent trend in leveraging divergence-based deep neural networks , convolutional neural networks , and small-sized models for efficient and accurate classification in BCI and medical imaging. His work emphasizes performance improvement with reduced channel counts, noise elimination, and real-time applicability in embedded systems. Scientific Awards: Excellent Oral Presentation Certificate, June 1, 2015 Advising and Grants: He is actively supervising 26 theses in progress, indicating a strong mentoring role. He has led multiple funded research projects, including those funded by ITU’s Technology Transfer Office (TTO) and Scientific Research Projects (BAP), such as 'Classification of Medical Images with Deep Learning Method in Embedded Systems' and 'New Approaches to Finding Optimal Protein Folding'. Labs and Research Teams: While specific lab names are not mentioned, his collaborative fingerprint and project leadership suggest he leads or is a key member of a research group focused on biomedical signal processing, neural networks, and intelligent systems at ITU.

• Information Security and Reliability
• Cyber Security
• Artificial Intelligence
• +۱۳ مورد دیگر

Prof. Dr. Murat Dener is a full Professor in the Department of Information Security Engineering at the Institute of Science and Technology, Gazi University, where he also serves as the Head of Department since 2020. He has been continuously affiliated with Gazi University since 2005, progressing from Research Assistant to full Professor in 2023. He is also a Member of the Gazi University Rectorate Quality Commission and a Researcher at the High Performance Computational Neuroscience Laboratory at the Neuroscience and Neurotechnology Excellence Joint Application and Research Center. His educational background includes a BSc, MSc, and PhD, all from Gazi University, with his doctoral studies partially conducted at Georgia Tech University, USA. He completed English language training at Georgia State University and has participated in multiple EU-funded international projects across Greece, Portugal, Belgium, Germany, and Kazakhstan. His research focuses on cutting-edge areas such as cyber security, artificial intelligence, internet of things, blockchain, big data analytics, and computational neuroscience. His work bridges theoretical research with practical innovation, exemplified by the development of Turkey’s first domestically produced wireless sensor node, "WiSeN", through a company he founded in 2014. The analysis of his recent publications reveals a strong trend toward integrating AI and deep learning into cyber defense, secure IoT systems, blockchain applications, and computational neuroscience. His work emphasizes real-world applicability, security, scalability, and innovation in smart city and critical infrastructure technologies. Academic Achievement Award, Georgia State University (2011) Second Prize, Gazi University Business Idea Competition (2014) Turkish First Prize, Junior Chamber International 'Ten Successful Young People of Turkey' (2014) World Top 20 Finalist, Junior Chamber International (Japan, 2014) First Prize, Young Entrepreneurship Category, Liyakat Association (2015) First Prize, Smart Buildings and Environment, TET R&D Project Market (2018) Prof. Dener actively advises master’s and doctoral students and has led numerous national and international research projects, including EU-funded collaborations. His leadership extends to editorial and peer-review roles in multiple journals. He is deeply involved in academic quality improvement as a member of the Rectorate Quality Commission and leads advanced research in computational neuroscience using high-performance computing platforms. He founded a technology company in 2014 under the Technopreneurship Capital Support Program, producing the first Turkish-made wireless sensor node (WiSeN), which led to several national innovation awards. His lab work centers on the High Performance Computational Neuroscience Laboratory, where he contributes to neurotechnology research, combining AI and neuroscience for brain-computer interface applications.

• Artificial Intelligence
• Neuroscience
• Circuits and Systems Theory

Neslihan Serap Şengör is a Professor at the Department of Electronics and Communication Engineering, Istanbul Technical University . Her work bridges Artificial Intelligence , Neuroscience , and Circuits and Systems Theory . Research areas include: Neuromorphic computing with Intel Loihi Basal ganglia and motor control modeling Spiking neural networks for hardware Cognitive process simulation Projects focus on: Hardware implementation of motor learning Computational models for Parkinson's disease Cortex structure simulation on neuromorphic chips Contact: sengorn@itu.edu.tr

• Instructional Technologies
• Artificial Intelligence in Education
• STEM Education
• +۳ مورد دیگر

Dr. Serkan Düzgün is an Associate Professor at Gazi University's Faculty of Education, Department of Basic Education, specializing in Classroom Education. He has previously worked as a part-time lecturer at Ankara Hacı Bayram Veli University and Ankara Yıldırım Beyazıt University. PhD, Master's, and Bachelor's degrees from Gazi University Active in instructional technologies, AI in education, STEM, and neuroscience applications Key contributor to Turkey's national education projects and civil society initiatives His research focuses on the integration of artificial intelligence in pedagogical practices, robotic coding platforms for K-12 education, and the cognitive impacts of neuroscience-based teaching methods . Recent work examines distance education challenges during the pandemic, learning style adaptations, and self-regulated learning in virtual environments. Current publications emphasize AI-driven educational tools , technology-enhanced literacy instruction , and virtual classroom dynamics . His 15 most recent articles (2021-2024) span topics like robotic coding in STEM education, emotional intelligence in remote teaching, and AI applications in qualitative research. Dr. Düzgün has conducted 108 projects, advised 3 theses, and actively participates in open-access initiatives and UN Sustainable Development Goals implementation through educational technology. He also played a pivotal role in establishing the "Voice of Turkish" Radio at Yunus Emre Institute.

• Artificial Intelligence
• Robotics
• Computer Vision
• +۴ مورد دیگر

Hulya Yalcin is an Assistant Professor in the Department of Mechanical Engineering at Istanbul Technical University. Her research focuses on artificial intelligence applications in robotics, computer vision, and precision agriculture. She leads projects in musculoskeletal modeling, plant phenology monitoring, and assistive technologies for elderly care. Her work contributes to UN Sustainable Development Goals related to innovation, health, and sustainable agriculture. Key projects include using deep learning for crop yield estimation and developing exergaming systems to improve elderly health. She has authored 52 research outputs and secured funding for initiatives like AISENSE (EU-funded exergames) and plant classification via computer vision. Publications span robotics control, medical engineering, and agricultural informatics. Notable contributions include knee orthosis gait learning via deep reinforcement learning and low-resource Turkish speech recognition improvements. As Principal Investigator, she manages projects on plant classification using CNNs, drone-based depth mapping, and multimodal assisted living systems. Her research bridges AI with practical applications in healthcare, agriculture, and robotics.

• Image Processing
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

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

• Signal Processing
• Biomedical Signal and Image Processing
• Artificial Intelligence Applications
• +۵ مورد دیگر

Prof. Dr. Aydın Akan is a Professor at the Department of Electrical and Electronics Engineering, Izmir University of Economics. He has held academic and leadership roles at Istanbul University (1996-2017), Izmir Katip Celebi University (2017-2020), serving as Department Chair, Dean of School of Engineering and Architecture, and Director of Biomedical Test and Calibration R&D Center. B.Sc. in Electronics Engineering (1988), Uludag University M.Sc. in Electronics and Telecommunications (1991), Technical University of Istanbul Ph.D. in Electrical Engineering (1996), University of Pittsburgh His research focuses on nonstationary signal processing , time-frequency analysis , and machine learning applications to biomedical engineering and wireless communications. Recent publications emphasize EEG-based diagnostics for neurological disorders, deep learning for biomedical signal classification, and synchronization analysis in brain activity. Article trends highlight interdisciplinary work bridging neuroscience , electrical engineering , and AI , with methodologies like time-frequency transforms, CNNs, and signal decomposition applied to epilepsy, ADHD, and Alzheimer's detection. Scientific honors include: TÜBİTAK scholarship (2004) Senior Member of IEEE Signal Processing and Engineering in Medicine & Biology Societies EURASIP Biomedical Image and Signal Analytics Committee member He has participated in numerous TÜBİTAK and university-funded research projects as principal investigator or researcher, contributed to books/journals, and serves on editorial boards including Elsevier's Digital Signal Processing Journal.

Şükriye KARAمشاهده پروفایل

پژوهشگر

• Computer Vision
• Robotics
• Fuzzy Logic
• +۳ مورد دیگر

Şükriye KARA is a Research Assistant at the Department of Electrical and Electronics Engineering, College of Engineering and Architecture, Eskisehir Osmangazi University, Turkey. Her research focuses on Computer Vision and Robotics , with additional contributions to Fuzzy Logic and Signal Processing . She holds a Bachelor's (2006) and Master's degree (2008) from Selcuk University, and a second Master's (2014) from New York University. Email: karas@ogu.edu.tr Office: Room B-306, Electrical and Electronics Engineering Department Research Themes: Her recent work in Medical Imaging includes breast cancer diagnosis using convex hull algorithms (2021) and wavelet domain feature extraction for movement classification (2018). Earlier contributions (2008-2010) focus on mathematical decompositions in Fuzzy Topology , particularly continuity analysis in ideal topological spaces. Academic Affiliations: Active in the Control and Automation Systems Research Group at Eskisehir Osmangazi University, she collaborates on projects related to electrical engineering and robotics.

Ertuğrul TAÇGINمشاهده پروفایل

استاد

• Occupational Safety
• Robotics
• Artificial Intelligence
• +۵ مورد دیگر

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.

• Artificial Intelligence
• Human-Computer Interaction
• Robotics
• +۱۲ مورد دیگر

Hatice Köse is a Professor at Istanbul Technical University in the Department of Artificial Intelligence and Data Engineering within the College of Computer and Informatics. She holds a PhD in Computer Engineering from Boğaziçi University and has been a key figure in advancing AI applications for human-centered technologies, particularly in assistive robotics and human-computer interaction. PhD in Computer Engineering, Boğaziçi University (2000–2007) MSc in Computer Engineering, Boğaziçi University (1997–2000) BSc in Computer Engineering, Boğaziçi University (1993–1997) Her research focuses on Artificial Intelligence , Human-Robot Interaction , and Assistive Technologies , with a strong emphasis on applications for children with autism and hearing impairments. She explores affective computing, emotion recognition using facial and physiological signals, and multimodal interaction frameworks. Her work integrates deep learning, signal processing, and robotics to develop inclusive technologies. Recent publications highlight trends in lightweight AI models for edge devices , gaze and emotion detection in children , and explainable machine learning in medical diagnosis . Her articles span top venues in AI, robotics, and multimodal interaction, reflecting a consistent focus on socially beneficial AI systems. EELISA Project Diversity Reward (2023) Best Paper Award, INISTA 2020 İTÜARI Teknokent Graduation Design Project Competition (2016) Necdet Eraslan Project Competition Honorable Mention (2011) Professor Köse has led numerous research projects funded by TÜBİTAK, EU, and university programs, including initiatives on AI-enabled manufacturing, teaching technologies to children with neurodevelopmental disorders, and sensor-based digital biomarkers for early detection. She has supervised multiple graduate students and research assistants, contributing to the development of next-generation AI researchers. She has also held administrative leadership roles such as Department Head and Education Coordinator. She is actively involved in research labs and teams focusing on socially assistive robotics , affective computing , and AI for accessibility , fostering interdisciplinary collaboration across computer science, psychology, and education.

• Wireless Communications
• Intelligent Signal Processing
• Biomedical Engineering
• +۳ مورد دیگر

Sanam MOGHADDAMNIA serves as an Assistant Professor in the Department of Electrical and Electronics Engineering at the Faculty of Engineering, Turkish-German University, Turkey. He holds a BSc from Tabriz University (2002), and both MSc (2006) and PhD (2012) degrees in Electrical Engineering from Leibniz Universität Hannover, Germany. Prior to his current position, he worked as a Research Assistant and Postdoctoral Researcher at Leibniz Universität Hannover from 2006 to 2018. His educational background includes: BSc in Electrical and Electronics Engineering from Tabriz University, Iran (1997-2002) MSc in Electrical Engineering and Information Technologies from Leibniz Universität Hannover, Germany (2003-2006) PhD in Electrical Engineering and Computer Science from Leibniz Universität Hannover, Germany (2006-2012) His research spans wireless communications, telemetry, intelligent signal processing, and data analysis with significant applications in healthcare (including ECG-based diagnostics, sepsis prediction, and gait analysis), telecommunications, and industrial sectors. He demonstrates expertise in machine learning applications for biomedical signal interpretation and has contributed to both theoretical wireless communications frameworks and practical medical device assessments. Analysis of his 2016-2024 publications reveals a strategic pivot toward biomedical engineering applications while maintaining core wireless communications research. His work shows increasing focus on non-invasive medical diagnostics using physiological signals, machine learning for healthcare analytics, and precision assessment of medical devices, alongside continued contributions to MIMO systems and channel estimation techniques. Scientific Awards: None mentioned in source material. He actively manages and acquires collaborative research projects with industrial partners across healthcare and telecommunications sectors. No student advisement details are provided in the available documentation. His research involves interdisciplinary collaboration with industrial partners but no specific laboratory or team names are documented in the source material.

Zeynep Yasemin Kahyaمشاهده پروفایل

استاد

• Biomedical Signal Processing
• Lung Acoustics
• Respiratory Sound Analysis
• +۴ مورد دیگر

Professor Zeynep Yasemin Kahya is a distinguished academic in the Department of Electrical and Electronics Engineering at Boğaziçi University's Faculty of Engineering. With a career spanning over three decades at Boğaziçi University, she has progressed from Assistant Professor to her current position as Professor. She has held significant administrative roles including Department Chair (2012-2021) and Deputy General Secretary (2008-2012). Dr. Kahya's research focuses on biomedical signal processing, particularly lung acoustics and respiratory sound analysis. PhD in Biomedical Electronics, Boğaziçi University (1981-87) MS in Electrical Engineering, Yale University (1980-81) BS in Electrical Engineering & Physics, Boğaziçi University (1976-80) Professor Kahya's research interests center on biomedical signal processing with specific emphasis on lung acoustics, respiratory sound analysis, and digital stethoscope design. Her work combines advanced signal processing techniques like wavelet transforms with clinical applications for pulmonary disease diagnosis. She has pioneered methods for pulmonary sound classification, crackle and wheeze detection, and respiratory sound parameterization. Her laboratory, the Lung Acoustics Laboratory (LAL), develops "smart stethoscope" diagnostic systems based on respiratory sounds. Her publications demonstrate a consistent research trajectory in respiratory sound analysis, with recent work focusing on machine learning approaches for pulmonary disease diagnosis. Professor Kahya has successfully translated her research into practical applications, including patented technologies for auscultation data acquisition systems and founding Electrosalus Biyomedikal, a company commercializing smart stethoscope technology. TÜBİTAK high school, undergraduate, and doctoral scholarships (1973-84) Fellowships from MIT, Yale, Stanford, and Caltech for undergraduate studies (1976) Fellowships from Yale and Princeton for doctoral studies (1980) Multiple research grants from Boğaziçi University Research Fund TÜBİTAK TEYDEP grants for smart stethoscope development Professor Kahya has supervised numerous PhD and Master's students, many of whom have worked on projects related to respiratory sound analysis and biomedical instrumentation. She has led multiple research projects funded by Boğaziçi University and external agencies like TÜBİTAK. Her laboratory, the Lung Acoustics Laboratory (LAL), brings together students from various disciplines to work on hardware and software projects related to "smart stethoscope" diagnostic systems.

Evin Şahin Sadıkمشاهده پروفایل

مدرس

• Biomedical Systems
• Biomedical Sensors
• EEG and Signal Processing
• +۲ مورد دیگر

Dr. Evin Şahin Sadık is a Lecturer at Dumlupınar University's Faculty of Engineering, Department of Electrical and Electronics Engineering. He holds a PhD in Electrical-Electronics Engineering and has been a Doctor Lecturer since 2023. His academic journey includes a BSc from Bilecik Şeyh Edebali University (2008-2012) and an MSc from Dumlupınar University (2013-2016). His research focuses on biomedical systems, EEG signal processing, and artificial intelligence applications in healthcare. Notable projects include investigating cognitive effects of aromatic scents using EEG and developing QCM-based biosensors for blood glucose monitoring. He teaches advanced machine learning, signal processing, and biomedical sensor courses. Key publications explore Alzheimer's detection via machine learning, EEG-based odor recognition, and glaucoma diagnosis using image analysis. He actively contributes to conferences and journals in biomedical engineering and AI. No awards or patents are listed. Advising records are unavailable, but his work emphasizes interdisciplinary collaboration in biomedical engineering and sensor technologies.

Shahram TAHERIمشاهده پروفایل

استادیار

• Biomedical Image
• Signal Processing
• Deep Learning
• +۲ مورد دیگر

Shahram TAHERI is an Assistant Professor in the Department of Computer Engineering at Antalya Bilim University (ABU), Turkey, since 2019. Previously, he served as a faculty member at Azad University, Iran, for 8 years. He holds a Ph.D. in Computer Engineering from Eastern Mediterranean University, a Master’s from Shiraz University, and a Bachelor’s from Shahid Bahonar University of Kerman. Research Interests: Biomedical Image Processing Signal Processing Deep Learning Pattern Recognition Neural Networks Key Trends in Publications: His work focuses on applying deep learning and neural networks to biomedical image and signal processing, particularly in age estimation, cancer histopathology, and animal classification. His research spans both multi-stage feature fusion and magnification-specific analysis.