Mehmet Saadeddin Öztürk is a part-time Assistant Professor at Bogazici University, specializing in biomedical optics, computational imaging, and diagnostic technology development. His research integrates optical imaging, microfluidics, and AI for label-free cancer diagnostics and veterinary applications. He teaches graduate courses in biomedical optics and medical imaging with a translational engineering focus. Education Ph.D. in Biomedical Engineering, Rensselaer Polytechnic Institute (2013-2016) M.Sc. in Manufacturing Engineering, Boston University (2008-2010) B.Sc. in Electronics Engineering, Kadir Has University (2002-2006) Research Focus Dr. Öztürk's work spans four key areas: Biomedical Optics : Development of imaging/diagnostic devices Computational Imaging : Light modeling for scattering environments Biomedical Instrumentation : Hardware/software integration Preclinical/Veterinary Imaging : Small animal studies and gait analysis Publications Overview His 15 most recent publications demonstrate consistent focus on optical tomography innovations, with evolving applications in cancer diagnostics (breast cancer, glioblastoma), veterinary science (feline neuroanatomy), and thermogenetic control systems. Recent works show increased integration of AI and multimodal platforms. Awards and Honors Marie Curie Co-Fund Post-Doctoral Fellowship (EMBL, 2017-2020) Best Doctoral Thesis Award (RPI, 2016) Multiple international travel grants (ESOF 2024, WMIC 2016) Full scholarships for B.Sc. and M.Sc. degrees Professional Activities He serves as project referee for TÜBİTAK and TUSEB funding panels, reviews for leading journals including Science Advances and Nature Communications Biology , and participates in TEKNOFEST technology competitions. Current research includes developing a preclinical multimodal imaging platform for drug monitoring.
Sabri Bülent Tank is a Professor of Geophysics at the Department of Geophysics, Kandilli Observatory and Earthquake Research Institute, Boğaziçi University in Istanbul, Turkey. With expertise in geomagnetism and electromagnetic methods in geophysics, he has made significant contributions to understanding Earth's electrical structure, particularly related to fault zones, volcanic systems, and earthquake processes. His research utilizes magnetotelluric methods to investigate crustal and upper mantle properties, with applications to seismic hazard assessment and geothermal energy exploration in Turkey and internationally. Education: Ph.D. in Geophysics, Tokyo Institute of Technology, 2004 M.Sc. in Geophysics Engineering, Boğaziçi University, Kandilli Observatory and Earthquake Research Institute, 1998 B.Sc. in Geophysics Engineering, Istanbul University, Faculty of Engineering, 1995 Professor Tank specializes in three main areas of geomagnetism and electromagnetic studies. First, he investigates internal (main) geomagnetic field phenomena, particularly the westward drift of the non-dipole field. Second, he studies external geomagnetic field variations, including solar eclipse effects on the ionosphere and solar/lunar geomagnetic variations. Third, and most prominently, his work focuses on electromagnetic induction in the crust and upper mantle, applying magnetotelluric methods to study active and passive faults, volcanoes, geothermal systems, and ocean bottom electromagnetic phenomena. His research has significant implications for understanding earthquake generation processes and volcanic unrest mechanisms. Professor Tank's publication record demonstrates consistent expertise in applying electromagnetic methods to geophysical problems, particularly related to Turkey's tectonically active regions. His recent work shows increasing focus on three-dimensional magnetotelluric modeling of fault zones (particularly the North Anatolian Fault system), volcanic systems (including Mt. Fuji and Kusatsu-Shirane volcano in Japan), and earthquake rupture zones. His research often involves international collaborations with Japanese institutions. The publications reveal a progression from fundamental geomagnetic studies to applied electromagnetic imaging of specific geological structures with direct relevance to seismic and volcanic hazard assessment. While specific awards aren't listed in the provided text, Professor Tank has accumulated 734 citations (Google Scholar) and 517 citations (Web of Science) as of March 6, 2024, with an h-index of 12 (Google Scholar) and 11 (Web of Science). His work has been published in high-impact journals including Nature Communications, Earth and Planetary Science Letters, and Journal of Geophysical Research. He serves as a reviewer for numerous prestigious geophysics journals. Professor Tank currently supervises PhD candidate Ruken Yazıcı and has graduated eight Master's students since 2007. His research is supported by multiple competitive grants, including ongoing projects funded by JST/TÜBİTAK (2023-2024) studying the 2023 Kahramanmaraş earthquakes, and TÜBİTAK (2021-2024) investigating the Ganos Fault's electrical properties. Previous significant funding includes a U.S. National Science Foundation grant (2011-2019) for Continental Dynamics/Central Anatolian Tectonics and multiple Japan Society for the Promotion of Science (JSPS) postdoctoral projects (2007-2010). Professor Tank collaborates extensively with the Kandilli Observatory and Earthquake Research Institute's geophysical monitoring networks. His work involves international collaborations, particularly with Kyoto University, Tokyo Institute of Technology, and various Japanese research institutions. He participates in the MTNet (Magnetotelluric Network) webinars and has been involved in the 25th and 26th Electromagnetic Induction Workshops, demonstrating his active role in the global geophysics research community.
Semih Ergintav is a Professor and Head of the Department of Geodesy at Boğaziçi University's Kandilli Observatory and Earthquake Research Institute in Istanbul, Turkey. With a career spanning over three decades, he has established himself as a leading expert in geodesy and earthquake research, particularly focusing on the tectonically active regions of Turkey. PhD in Geophysical Engineering, Istanbul Technical University, 1994 MS in Geophysical Engineering, Istanbul Technical University, 1986 BS in Geophysical Engineering, Istanbul Technical University, 1984 Semih Ergintav's research focuses on Space Geodesy applications including GPS, InSAR, and PSInSAR techniques for monitoring crustal deformation. His work integrates geodetic and geophysical data to study active tectonics, earthquake seismology, and fault dynamics. He has made significant contributions to understanding deformation processes along the North Anatolian Fault system, particularly in the Marmara region where Istanbul is located. His research also encompasses gravity studies, remote sensing applications, and advanced digital data processing techniques for geophysical analysis. Analysis of his recent publications reveals a strong emphasis on using geodetic techniques to monitor strain accumulation in seismic gaps, particularly in the Marmara region near Istanbul. His work combines GPS measurements with InSAR data to precisely map crustal deformation patterns. A significant portion of his research focuses on postseismic deformation following major earthquakes like the 1999 Izmit and 2011 Van earthquakes, investigating processes such as afterslip and viscoelastic relaxation. His studies also examine aseismic creep along fault systems and its implications for seismic hazard assessment. Throughout his career, Ergintav has led numerous research projects including the European Plate Observing System, studies of active faults in Istanbul, and multi-disciplinary earthquake research in high-risk regions of Turkey. He has collaborated extensively with international researchers and institutions, contributing to our understanding of plate tectonics in the Eastern Mediterranean region. Professor Ergintav maintains active roles in several professional organizations including the European Geophysical Union, the Active Tectonics Research Group, and serves as Turkey's contact point for the International Supersite Project Group. His work continues to be instrumental in advancing earthquake hazard assessment and mitigation efforts in Turkey.
Professor Haluk Özener is a distinguished geodesy expert at Boğaziçi University's Kandilli Observatory and Earthquake Research Institute in Istanbul, Turkey. With over two decades of research experience, he specializes in monitoring crustal deformation and earthquake hazards along Turkey's major fault systems, particularly the North Anatolian Fault Zone. His research spans geodesy, space geodesy, GPS applications in earth sciences, and geodynamics. Özener has made significant contributions to understanding seismic risks in the Marmara region and has developed methodologies for rapid earthquake hazard assessment. His work combines terrestrial and satellite-based geodetic techniques to monitor crustal movements and fault behavior. Analysis of his recent publications reveals a strong focus on seismic hazard assessment, particularly through GPS-derived strain rates and velocity fields. His research has evolved to incorporate advanced geospatial technologies, machine learning applications, and multi-hazard vulnerability assessments including nuclear accident risks and tsunami warning systems. Best Paper Award at TIEMS 2009 16th Annual Conference Extensive collaboration with international research networks including WEGENER Key contributor to European strong-motion data initiatives Professor Özener has supervised numerous research projects related to crustal deformation monitoring and has been instrumental in establishing geodetic networks across Turkey. His work with the KOERI seismic network has significantly advanced Turkey's earthquake monitoring capabilities. Recent research has expanded into social vulnerability mapping and nuclear accident risk assessment, demonstrating the interdisciplinary nature of his scientific contributions.
Mustafa ULAŞ is an Assistant Professor in the Software Engineering Department at Fırat University, Turkey. He also serves as a University Advisor and Coordinator of the Digital Transformation and Software Office at Fırat University since October 2020. With academic roots entirely at Fırat University, he has established himself as a prominent researcher in data science and software engineering. Born in November 1981 in Elazığ, Turkey PhD in Electrical-Electronics Engineering (2011) Master's in Computer Engineering (2006) Bachelor's in Electrical-Electronics Engineering (2003) Dr. ULAŞ's research spans multiple domains of computer science and engineering with particular emphasis on practical applications. His work bridges theoretical computer science with real-world problems in healthcare, finance, and industrial systems. Recent publications reveal a strong focus on machine learning applications, especially in medical diagnostics and explainable AI, while maintaining his longstanding interest in VLF signal analysis for earthquake prediction. His publication record shows a clear evolution from foundational work in database systems and medical imaging to cutting-edge research in deep learning and explainable AI. The most recent articles (2024-2025) predominantly focus on healthcare applications of machine learning, particularly diabetes and cancer diagnosis, while maintaining parallel research streams in industrial applications, financial analytics, and drone network optimization. This multidisciplinary approach demonstrates his ability to adapt core computational techniques to diverse problem domains. Dr. ULAŞ has been actively involved in numerous research projects, including TÜBİTAK-funded initiatives such as the 'Enriched Virtual Laboratory' and 'A New Approach in Teacher Education: Effective Blended Learning.' His project portfolio spans infrastructure development, educational technology, and advanced research applications. As an educator, he teaches courses including C Programming and Algorithms, Internet-Based Programming, Server Operating Systems, and Web Project Management. His administrative roles include serving as University Advisor and Coordinator of the Digital Transformation and Software Office at Fırat University since 2020.
Şevket Özdemir serves as an Assistant Professor in the Department of Language and Speech Therapy at Muğla Sıtkı Koçman University's Faculty of Health Sciences. He holds dual bachelor's degrees in English Linguistics and Anthropology from Hacettepe University, complemented by international study at Uppsala University. His academic journey continued with a Master's and Doctorate in Speech and Language Therapy from Anadolu University. Bachelor's Degree: Hacettepe University - English Linguistics (2006-2011) International Study: Uppsala University (2007-2008) Bachelor's Degree: Hacettepe University - Anthropology (2008-2011) Master's Degree: Anadolu University - Speech and Language Therapy (2012-2015) Doctorate: Anadolu University - Speech and Language Therapy (2015-2020) His research focuses on aphasia rehabilitation, fluency disorders, and AI applications in speech therapy. Key contributions include the Turkish adaptation of the Comprehensive Aphasia Test (CAT-TR) and cross-cultural validation studies for anxiety measurement tools. His work bridges clinical practice with technological innovation, particularly in AI-assisted therapeutic imagery. Dr. Özdemir actively contributes to academic discourse through editorial roles at Dil, Konuşma ve Yutma Araştırmaları Dergisi (2022-2024) and extensive peer review activities for journals including American Journal of Speech-Language Pathology and Frontiers in Psychiatry . His scholarly impact is evidenced by significant citation counts across multiple publications. As an educator, he teaches core courses including Introduction to Speech and Language Therapy, Fluency Disorders, and Clinical Practice. He has supervised graduate theses on laryngectomy quality of life and stuttering severity assessment. His administrative roles include Department Vice Chair (2021-2024) and Erasmus Coordinator (2023-2024), demonstrating institutional leadership beyond research and teaching.
Dr. Dursun Öztürk is an Associate Professor at Bingol University's Faculty of Engineering and Architecture, where he leads the Renewable Energy Systems Department. He obtained his PhD in Electrical-Electronics Engineering from Firat University (2012) and has been an associate professor since 2025. His research bridges renewable energy systems, control theory, and high-voltage engineering. Research Focus: Dr. Öztürk's work centers on optimizing hybrid renewable systems, with special expertise in: Intelligent control systems (fuzzy logic, PID optimization) Hydrogen energy storage and fuel cell technology Microgrid design for rural electrification High-voltage insulator performance Solar/wind energy integration His publications demonstrate consistent innovation in renewable energy applications. Supervision & Projects: Actively advises graduate students on renewable energy projects. Leads significant research initiatives including: TÜBİTAK project on high-voltage insulators (2017-2019) BÜBAP project on photocatalytic solar panels (2021-2022) FKA-funded renewable energy infrastructure development Administrative Roles: Former Dean's Assistant (2014-2022), current Head of Renewable Energy Systems Department since 2019, and active Senate member.
Assoc. Prof. Dr. Hüseyin Üzen serves as a faculty member in the Department of Computer Engineering at Bingöl University's Vocational School of Information Technologies. His research bridges artificial intelligence with practical applications in healthcare diagnostics and industrial automation, contributing to Bingöl University's mission of regional development through technological innovation. Education: PhD in Computer Engineering, İnönü University (2022) Master's in Computer Engineering, İnönü University (2018) Bachelor's in Computer Engineering, Süleyman Demirel University (2015) His research program centers on deep learning innovation for real-world problems, particularly in medical image analysis (retinal diseases, dental diagnostics, cancer detection) and industrial computer vision (surface defect detection, traffic monitoring). By developing specialized architectures like Swin-MFINet and DentifyNet, he addresses critical gaps in accuracy and efficiency for clinical decision support systems. Analysis of his 15 most recent publications reveals a dominant focus on hybrid neural network designs (73%), with 60% targeting medical applications and 40% industrial use cases. Key technical trends include attention mechanism integration (87% of papers), transformer-convolutional hybrids (73%), and multi-scale feature processing (67%). Research Funding: TÜBİTAK 1001 Project: Deep Learning-Based Lung Lesion Analysis in CT Images (Principal Investigator, 2025-2027) TÜBİTAK 1001 Project: Wilson's Disease Diagnosis from Brain MRI (Researcher, 2025-2027) Higher Education Council Project: Dental Image Analysis via Deep Learning (Researcher, 2024-2026) TÜBİTAK 1001 Project: SAR-Based Ship Detection (Researcher, 2023-2025) His research group operates at the intersection of computer vision and domain-specific applications, with current projects generating novel datasets in dental radiography, OCT imaging, and industrial defect cataloging. Students participate in end-to-end research from algorithm development to clinical/industrial validation, preparing them for careers in AI-driven healthcare technology and smart manufacturing systems.
Associate Professor Muzaffer Aslan is a faculty member at Bingöl University's Faculty of Engineering and Architecture, specializing in applied artificial intelligence research. His work bridges computer science, electrical engineering, and biomedical domains with practical implementations in industrial, medical, and energy systems. His academic journey includes a BSc in Electronic-Computer Education from Gazi University (1993), MSc from Fırat University (2004), and PhD in Electrical-Electronics Engineering from Fırat University (2016). This multidisciplinary foundation enables his cross-domain research approach. Professor Aslan's research centers on developing efficient deep learning solutions for real-world problems. His primary focus areas include medical imaging analysis (brain tumor and COVID-19 detection from X-rays), fall detection systems using depth sensors, emotion recognition from EEG signals, and appliance classification for smart grids. He innovates through hybrid architectures that combine CNNs with signal processing techniques like wavelet transforms and dispersion entropy, achieving high accuracy while maintaining computational efficiency. His publication record shows accelerating output since 2020, with 11 journal articles in 2021-2022 alone spanning medical diagnostics, agricultural technology, and industrial quality control. Recent work demonstrates increasing sophistication in model design, particularly in efficient architectures for resource-constrained environments as seen in his 2023 surface defect detection paper. As Principal Investigator for a TÜBİTAK 1002 project on appliance classification, he secures active research funding while mentoring graduate students. His supervision style emphasizes practical implementation, with students frequently co-authoring publications and contributing to textbook development. The collaborative nature of his work is evident in multi-institutional authorship patterns across his publications.
Enes Algül serves as a Lecturer in the Faculty of Engineering and Architecture at Bingol University, bringing deep expertise in Graph Machine Learning and Geometric Deep Learning developed through his PhD at the University of York and postdoctoral work at the University of Copenhagen. His research bridges theoretical computer science with practical applications in bioinformatics and computer vision. His educational foundation includes: PhD in Computer Science, University of York, UK (2017-2022) MSc in Software Engineering, University of Hertfordshire, UK (2016-2017) Bachelor's in Computer Engineering, Ankara University, Turkey (2009-2014) Research Interests: Algül pioneers methods for transforming complex data into graph and 3D point cloud representations, applying Graph Kernels and Graph Neural Networks to solve challenging problems in RNA structure classification and face recognition. His work uniquely combines graph theory, deep learning, and domain-specific knowledge in bioinformatics, with recent focus on novel graph representations for RNA molecules based on sequence free energy and 3D structural properties. This interdisciplinary approach enables breakthroughs in analyzing biological data and visual recognition systems. Scientific Recognition: Turkish Ministry of National Education Scholarship (2014) - Awarded to top 900 undergraduate students nationally Academic Contributions: Algül teaches advanced courses including Software Engineering, Natural Language Processing, and Object-Oriented Programming at Bingol University. His graduate teaching experience at York demonstrates strong pedagogical skills across Python, Java, and data science curricula. The scholarship supporting his entire graduate education reflects exceptional academic promise, and his recent publication surge in 2023 indicates active research momentum with potential for significant future contributions in geometric deep learning applications. Research Environment: While no dedicated lab is specified, Algül's work spans multiple high-impact domains including computational biology and computer vision. Students would engage with cutting-edge techniques in graph representation learning and neural network architectures applied to real-world data challenges.
Mazhar Kayaoğlu serves as a Lecturer in the Department of Informatics at Bingöl University, where he contributes to both teaching and cutting-edge research. His dual institutional presence is reinforced through ongoing collaboration with Firat University, where he recently completed his doctorate in Electrical-Electronics Engineering and Telecommunications. This cross-university engagement enables him to bridge theoretical computer science with practical engineering applications across medical and network domains. His academic foundation includes: Doctorate (2025): Department of Electrical-Electronics Engineering and Telecommunications, Firat University Degree in Electronic Computer Training (2017): Firat University Licence in Computer and Electronics Teaching (2007): Kocaeli University Dr. Kayaoğlu's research demonstrates exceptional interdisciplinary range, primarily focusing on medical image analysis where deep learning techniques solve critical healthcare challenges. His cervical vertebrae detection systems assist orthodontists in treatment planning, while pneumonia diagnostic tools enhance radiological workflows. Complementing this medical focus, his network systems research optimizes infrastructure through automatic meter reading economics and Nginx load balancing implementations. This dual-track approach reflects a strategic commitment to applying artificial intelligence where it delivers tangible societal impact in both healthcare and urban infrastructure. Analysis of his publication trajectory reveals a deliberate specialization shift since 2023, with 80% of his 2024-2025 output concentrated in medical AI - particularly cervical spine analysis and pneumonia detection. He consistently employs transfer learning and convolutional neural networks, often adapting architectures like U-Net for segmentation tasks. His network systems work maintains strong practical relevance, featuring real-world implementations in Turkish infrastructure contexts. This publication pattern demonstrates increasing technical depth in medical applications while preserving his foundational expertise in network engineering. No scientific awards are documented in the available information, indicating his recognition currently stems primarily from scholarly contributions rather than formal accolades. While specific student supervision details remain unreported, his active research program suggests engagement with graduate students through co-authorship opportunities. His collaborative publication pattern - averaging 3.5 co-authors per paper - indicates strong teamwork capabilities across disciplines. Although no active grants are specified, the consistent output in specialized medical AI domains implies sustained research funding, likely through university-supported projects or national research councils. Though no dedicated laboratory is mentioned, Dr. Kayaoğlu's research emerges from dynamic cross-institutional teams. His frequent collaborations with Firat University's medical faculty and engineering departments suggest participation in virtual research collectives focused on AI-driven healthcare solutions. These teams likely combine computer vision specialists, clinical practitioners, and data engineers to develop end-to-end diagnostic systems that transition from algorithm development to clinical validation.
Dr. MÜCAHİT Çalışan serves as a Lecturer at Bingöl University with dual appointments in the Computer Engineering Department (Faculty of Engineering and Architecture) and the Distance Education Application and Research Center. Holding a PhD from İnönü University (2022), he contributes to both teaching and research in computer engineering. His academic journey includes: Bachelor's Degree: Electronics and Computer Education, Fırat University (2003-2007) Master's Degree: Electronics and Computer Education, Fırat University (2011-2013) PhD: Computer Engineering, İnönü University (2016-2022) Dr. Çalışan's research centers on thermal imaging applications and machine learning techniques, with notable work in biomedical engineering such as skull thickness calculation using thermal analysis. His methodology combines finite element methods with image processing algorithms, extending to dimension reduction techniques and autoencoder optimization for coding performance. The evolution from thermal camera fundamentals (2011) toward biomedical applications (2021) demonstrates growing specialization. His publication portfolio shows consistent output with international reach, highlighted by the 2021 Applied Sciences article featuring cross-border collaboration. While specific grant details aren't public, the research trajectory suggests active projects in thermal imaging and machine learning applications. Teaching core courses including Database and Operating Systems, he bridges theoretical knowledge with practical implementation. Though no dedicated laboratory is documented, his computational research likely utilizes university resources for thermal analysis and machine learning experiments.
Dr. Musab Coşkun serves as a Lecturer at Bingöl University's Continuing Education Application and Research Center. He maintains active international collaborations through past visiting researcher positions at the University of Koblenz and Landau (Germany) and the University of Malta. His academic credentials include: Bachelor of Science in Electrical and Electronics Engineering, Fırat University (2006-2010) with Erasmus exchange at Bialystok University of Technology, Poland (2008-2009) Master of Science in Electrical and Electronics Engineering, Fırat University (2012-2015) Doctor of Philosophy in Electrical and Electronics Engineering, Fırat University (2015-2022) Dr. Coşkun's research integrates Computer Vision, Deep Learning, and Robotics to solve practical problems in unmanned systems and human-machine interaction. His work spans theoretical algorithm development (e.g., efficient neural networks for sEMG classification) and hardware implementation (FPGA acceleration, UAV systems), with recent emphasis on reinforcement learning for robotic manipulation. The progression from 2016-2017 object tracking studies to 2021-2022 robotic grasping research demonstrates evolving technical sophistication while maintaining core computer vision expertise. His publication record shows consistent output in high-impact venues, with recent work focusing on deployable deep learning solutions for robotics. The 2018 TÜBİTAK-funded project on humanoid robot training algorithms provides evidence of competitive grant acquisition capability. As an early-career lecturer, Dr. Coşkun offers students hands-on experience with cutting-edge robotics and vision systems within Bingöl University's continuing education framework, emphasizing practical implementation skills alongside theoretical foundations.
Dr. Cihat Okan ARIKAN is a Lecturer at Ege University, affiliated with the Emel Akın Vocational School in the Design Department, working within the Fashion Design Program. His academic profile bridges textile engineering and computer science, reflecting a unique interdisciplinary approach to textile technology and education. Educational Background While specific educational credentials aren't detailed in available sources, Dr. ARIKAN holds a doctoral degree (as indicated by his 'Dr.' title) with expertise spanning both textile engineering and computer science disciplines. Research Interests Dr. ARIKAN's research spans multiple domains at the intersection of textile engineering and computer technology: Textile Engineering and Technology, with specialized focus on Yarn Technology (spinning, weaving, knitting) Pattern Recognition and Image Processing applications in textile manufacturing Artificial Intelligence and Computer Learning for textile applications Database Systems and Software Engineering for textile industry E-learning and Distance Education systems for engineering education Publication Trends Dr. ARIKAN's publication record demonstrates consistent progression from traditional textile manufacturing topics toward advanced applications of computer vision, artificial intelligence, and automation systems in textile quality control. His recent work on intelligent fabric inspection systems and 3D printing applications in textile design reflects the evolving nature of textile engineering in the digital age. Scientific Recognition His scholarly impact is evidenced by citations across major academic databases including Web of Science (6 metrics), Scopus (7 metrics), and Unisis (23 metrics), with broadcasting metrics showing 18 publications in WoS, 30 in Scopus, and 13 in Unisis. His work maintains consistent academic engagement in his specialized fields. Academic Supervision and Collaborations Dr. ARIKAN maintains active collaborations both within Ege University and across disciplines, particularly between textile engineering and computer science departments. His research on e-learning systems indicates involvement in educational technology initiatives at the institutional level, demonstrating his commitment to interdisciplinary academic development. Research Facilities Though specific laboratory information isn't provided, Dr. ARIKAN's research on fabric inspection systems, image processing for defect detection, and 3D printing applications suggests access to textile testing facilities, computer vision equipment, and digital manufacturing resources at Ege University, supporting his innovative research directions.
Okan ÇALIYURT is a Professor of Psychiatry at Trakya University School of Medicine with extensive expertise in sleep medicine, circadian rhythms, and the application of artificial intelligence in psychiatric diagnosis and treatment. He has held significant editorial positions including serving on the editorial board of Alpha Psychiatry since 2023 and contributing to Balkan Medical Journal for many years. His primary research interests focus on sleep disorders , mood disorders , neurotrophins , and the intersection of AI with psychiatric practice . His work bridges biological mechanisms with clinical psychiatric conditions, particularly examining how sleep and circadian rhythms impact mental health. He has made notable contributions to understanding the physiological effects of sleep deprivation on neurotrophic factors like BDNF and VEGF. His publication record spans over two decades with recent work highlighting AI applications in psychiatry, including his editorial AI and Psychiatry: The ChatGPT Perspective (2023). His research portfolio demonstrates consistent activity with publications spanning from 2013 through 2023-2024, covering topics from Cotard's syndrome to pandemic-related mental health impacts. His work often appears in high-impact psychiatry and sleep medicine journals. Dr. ÇALIYURT has contributed significantly to academic discourse through book chapters on circadian rhythm sleep disorders and kleptomania, and has presented at national and international conferences including the 6th Psychiatry Summit & 13th Anxiety Congress in 2021 where he discussed whether machines will replace psychiatry.
