Onur Varol is an Assistant Professor at Sabanci University's Computer Science Department and leads the VIRAL Lab, which focuses on computational social science, network science, and machine learning. He has affiliations with the Center of Excellence for Data Analytics. His research spans social bot detection, misinformation analysis, and online behavior modeling.
Dr. Aykut Koç is an Associate Professor at the Department of Electrical and Electronics Engineering and a faculty member of the National Magnetic Resonance Research Center (UMRAM) at Bilkent University, Turkey. He leads the AykutKoc Lab, focusing on interdisciplinary research at the intersection of machine learning, signal processing, natural language processing, and graph signal processing. Education: B.S. in Electrical and Electronics Engineering (2005, Bilkent University); M.S. in Electrical Engineering (2007), M.S. in Management Science and Engineering (2009), and Ph.D. in Electrical Engineering (2011) under Professor Lambertus Hesselink at Stanford University; LL.B. in Law (Ankara University). His research integrates mathematical signal processing techniques (e.g., fractional Fourier and linear canonical transforms) with modern machine learning architectures like transformers and graph neural networks. Recent work explores semantic communication systems, bias mitigation in legal language models, and cross-modal applications in biomedical imaging and radar technology. Dr. Koç has published extensively in IEEE and Springer journals, with recent articles analyzing Fourier-enhanced transformers, graph-based NLP methods, and time-vertex signal analysis. His work addresses both theoretical innovations and practical applications, including schizophrenia diagnosis, legal outcome prediction, and maritime surveillance. Scientific Awards: Science Academy Young Scientists Award (BAGEP), 2023. He has supervised numerous graduate and undergraduate researchers, many of whom have transitioned to top-tier institutions such as MIT, UCLA, and TU Darmstadt. Dr. Koç actively serves as Associate Editor for multiple IEEE journals and participates in conference program committees, including EMNLP's Natural Legal Language Processing (NLLP) workshop.
Caner Ünlü is an Associate Professor in the Department of Chemistry at Istanbul Technical University with 39 publications and 10 active research projects through 2025. His work focuses on quantum dot synthesis, photophysical characterization, and applications in environmental sensing and renewable energy systems. Research interests center on carbon dots, chalcogenide quantum dots, and their interactions with biological systems. Key areas include tunable emission design, photosynthetic enhancement for algae biomass production, eco-friendly ATP sensing, and micropollutant removal. His methodology integrates experimental synthesis with computational modeling and machine learning for nanomaterial optimization. Recent publications (2024-2025) demonstrate strong thematic coherence in quantum dot engineering for specific functionalities: dopant-driven metal ion sensing, defect state manipulation in chalcogenides, and spectral modulation of photosynthetic complexes. This work bridges nanomaterials science with biotechnology and environmental engineering. Scientific awards: None mentioned in source material. Ünlü has supervised 14 research students and secured multiple grants including TÜBİTAK funding for quantum dot applications in solar cells and environmental remediation. Current projects involve quantum dot integration with metal-organic frameworks and development of fuel-marking nanomaterials. While specific lab names are unreported, his collaborative projects indicate active participation in interdisciplinary teams advancing quantum dot technology for energy and environmental solutions.
Can Güler is an Assistant Professor in the Department of Lifelong Learning and Adult Education at the Faculty of Education, Anadolu University, Turkey. Previously, from 2002 to 2023, he served as a Lecturer in the Department of Distance Education at the Faculty of Open Education, Anadolu University. His academic career spans over two decades with continuous contributions to open and distance education systems. His educational background includes: Bachelor's degree in Computer and Instructional Technologies Education, Anadolu University (2002) Master's degree in Distance Education, Institute of Social Sciences, Anadolu University (2007) Ph.D. in Distance Education, Institute of Social Sciences, Anadolu University (2022) Güler's research centers on open and distance learning methodologies, educational technology integration, and instructional material development. He specializes in video-based learning systems, interactive media design, and gamification strategies for enhancing learner engagement. His work addresses practical challenges in digital content creation and accessibility for diverse learner demographics, particularly adult populations. Analysis of his publication trajectory reveals consistent innovation in multimedia applications for distance education, with recent emphasis on generative AI awareness among educators and interactive video transformation techniques. His research frequently employs design-based methodologies and institutional case studies from Anadolu University's open education infrastructure. Scientific Awards: None mentioned in available sources. Advising and Grants: No information provided regarding student supervision or research funding in current documentation.
Prof. Dr. Yavuz Yakut serves as full-time Professor and Head of the Department of Physiotherapy and Rehabilitation at Hasan Kalyoncu University's Faculty of Health Sciences since 2016. Previously, he held academic positions at Hacettepe University from 1985 to 2016, progressing from Research Assistant to Professor, while concurrently serving on national committees including the Ministry of Health and Ministry of Finance Budget Implementation Commissions (1997-2003) and YÖK Physiotherapy Sub-Commission (2013-2016). His educational foundation includes a Bachelor's (1984), Master's (1987), and PhD (1990) in Physiotherapy and Rehabilitation, all completed at Hacettepe University. Yakut's research demonstrates exceptional breadth across rehabilitation science, with concentrated expertise in biomechanics and scoliosis rehabilitation . His work significantly advances neurological rehabilitation for conditions like multiple sclerosis and cerebral palsy, while pioneering applications in burn rehabilitation and orthotics/prosthetics . Recent publications reveal strategic integration of biopsychosocial models and telerehabilitation , particularly addressing pandemic-related challenges and chronic disease management across diverse populations. Analysis of his 2023-2025 publications shows consistent interdisciplinary innovation: validating cross-cultural assessment tools (e.g., Turkish translations of scoliosis and ADL questionnaires), developing novel exercise protocols (dance therapy, cognitive exercise therapy), and investigating rehabilitation responses in complex cases including HIV, rheumatic diseases, and post-earthquake trauma. His methodology frequently combines biomechanical analysis with patient-centered outcomes, demonstrating particular rigor in controlled trials for spinal deformities and burn recovery. His leadership extends beyond direct research through committee roles shaping national rehabilitation policy and educational standards, including his current departmental leadership and recent systematic review on physiotherapy distance education during pandemic disruptions.
Başar Öztayşi is a Professor at the Department of Industrial Engineering , Istanbul Technical University , with expertise in fuzzy logic, multi-criteria decision making, and decision science. He has held administrative roles including Associate Professor (2017–present), Deputy Director of the Institute (2016–2017), and Assistant Professor (2013–2017). Fields of Study : Fuzzy Logic, Multi-criteria Decision Making, Decision Science Contact : oztaysib@itu.edu.tr , +90 212 293 1300 Research Interests focus on applying fuzzy set theory to complex decision problems, including financial management, risk assessment, and smart city energy systems. His work extends to industry 4.0 applications and process mining in e-commerce. Recent Publications (2024) analyze fuzzy approaches in financial management, risk assessment, and Industry 4.0, with subfields spanning bibliometric trends, allocation optimization, and sustainable energy planning. Earlier works explore AHP matrix consistency, file distribution models, and customer segmentation. Awards : Best Paper Award, FLINS 2018 Science - Art Awards
Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.
Asst. Prof. Zehra Evrim Kanat serves as an Assistant Professor in the Textile and Fashion Design Department at Canakkale Onsekiz Mart University's Faculty of Fine Arts since 2020, following research assistant roles at Tekirdağ Namik Kemal University (2014-2020) and Ege University (2009-2014). Her expertise bridges academic research and industry applications in textile engineering. Her educational foundation includes: Doctorate in Textile Engineering from Ege University (2008-2013) Postgraduate in Textile Engineering from Ege University (2005-2007) Undergraduate in Textile Engineering from Ege University (1997-2002) Dr. Kanat's research centers on textile engineering and design, with specialized focus on thermal and moisture management properties of fabrics. She investigates yarn technology, cloth construction, and smart textile applications to enhance comfort in sportswear and technical garments. Her methodological approach integrates artificial neural networks and statistical modeling for predictive analysis of fabric behavior under varying humidity conditions, contributing significantly to thermophysiological comfort research. Publication trends reveal consistent advancement in thermal resistance modeling of knitted and woven fabrics, with recent expansion into smart textiles for sports applications and biomimetic design principles. Her work demonstrates strong interdisciplinary connections between textile science, materials engineering, and functional apparel design. Her research leadership includes: EU-supported project on Textile Insights and Future Aspects (2023-2024) Study on Hatay Silk's fiber properties versus Chinese-Japanese hybrid silk (2022-2023) TUBITAK-funded expert system for woven fabric defect diagnosis (2017-2018) Multiple projects on moisture management properties of technical textiles Dr. Kanat actively contributes to academic discourse through peer review for leading textile journals and participates in interdisciplinary art exhibitions that explore cultural and historical textile narratives.
Professor Hakan Ali Çırpan is a distinguished faculty member at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where he serves as Professor in the Department of Electronics and Communication Engineering. He also holds the position of Vice Dean at Istanbul Technical University since 2021. With over three decades of academic experience, Professor Çırpan has established himself as a leading researcher in signal processing and communications. His educational background includes: PhD from Stevens Institute of Technology (1993-1997) Master's degree in Electrical-Electronic Engineering (with thesis) from Istanbul University (1989-1992) Bachelor's degree in Electrical and Electronic Engineering from Uludağ University (1985-1989) Professor Çırpan's research spans multiple domains within signal processing and communications. His primary interests include wireless communications, radar systems, machine learning applications in communications, and electronic warfare. His work on channel estimation, orthogonal frequency division multiplexing, and maximum likelihood methods has been particularly influential. He has pioneered research in areas such as source localization, spectrum sensing, and physical layer security. His recent work focuses on 5G/6G networks, AI-enhanced communications, and integrated sensing and communication systems. Analysis of his recent publications (2023-2025) reveals a strong focus on next-generation wireless technologies, particularly 5G/6G networks, AI integration in communications, and electronic warfare applications. His research demonstrates a consistent pattern of addressing fundamental challenges in signal processing while adapting to emerging technological needs. A significant portion of his recent work involves machine learning applications for spectrum management, optimization techniques for radar systems, and novel approaches to network slicing and resource allocation. His notable scientific achievements include: ASELSAN ACADEMY THESIS COMPETITION WINNER (2020) Professor Çırpan has supervised 59 theses throughout his career, mentoring numerous graduate students in the fields of signal processing and communications. He has secured significant research funding, including the "AI-Enhanced 5G/6G Networks with Integrated Camera and ISAC Systems" project (2023-2024) and the "Railway Vehicle Infrastructure New Generation Secure Communication Systems" TÜBİTAK project with a budget of ₺955,000. His research has practical applications in defense systems, railway communications, and next-generation wireless networks. His laboratory work focuses on wireless communications systems, radar signal processing, and AI-enhanced communication technologies. Professor Çırpan leads research teams working on projects related to 5G/6G networks, electronic warfare countermeasures, and secure communication systems. His group collaborates with industry partners like ASELSAN and conducts research with practical applications in national defense and critical infrastructure.
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.
Prof. Dr. Ahmet ÖZMEN is a Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Software Engineering. He has held various administrative positions including Head of the Software Engineering Department (2019-2028) and Director of the Computer Research and Application Center (2019-2022). With extensive experience in academia since 1991, he has made significant contributions to computer vision, traffic monitoring systems, and sensor technologies. Sakarya University: Professor (2019-present), Associate Professor (2011-2019) Dumlupınar University: Assistant Professor (2001-2011), Research Assistant (2000-2001, 1993-1998) Istanbul Technical University: Research Assistant (1991-1993) Prof. ÖZMEN's research spans computer vision applications for traffic monitoring, indoor air quality systems, parallel computing, and sensor technologies. His work bridges theoretical computer science with practical engineering applications, particularly in developing vision-based systems for nighttime vehicle detection, traffic flow monitoring, and environmental sensing. His interdisciplinary approach combines machine learning, image processing, and embedded systems to solve real-world problems in transportation and environmental monitoring. His publication record shows a clear evolution from parallel and distributed systems in his early career to computer vision and sensor applications in recent years. The majority of his recent work focuses on traffic monitoring systems using computer vision techniques, particularly for nighttime conditions, and indoor air quality monitoring systems using sensor networks. His research demonstrates strong industry and societal relevance, with applications in smart transportation, environmental protection, and educational technology. TÜBİTAK Publication Awards (2006, 2008, 2009, 2010) Physical implementation award from TÜBİDER (2008) Microsoft Certified Professional Certificate (2005) YÖK overseas study scholarships (1993, 1998) Elginkan graduate scholarships (1990, 1991) Prof. ÖZMEN has supervised numerous graduate students across multiple institutions, with a focus on practical engineering problems. His research has been supported by various projects including TÜBİTAK projects, institutional research grants, and industry collaborations. He has led significant research initiatives in traffic monitoring systems, indoor air quality monitoring, and educational technology platforms. His administrative leadership has included directing research centers and shaping curriculum development in software engineering. His work has involved establishing research teams focused on computer vision applications, sensor network development, and educational technology. These teams have produced numerous publications, developed practical systems, and trained the next generation of computer engineers. Current research directions include advanced traffic monitoring systems using deep learning and multi-camera setups for urban planning applications.
Professor Serdar Özoğuz is a full faculty member at the Department of Electronics and Communication Engineering , Istanbul Technical University . Holding a Ph.D. from ITU (2000) and a M.Sc. from ITU (1993) , he has taught courses like Active Network Synthesis , Basics of Electrical Circuits , and Scientific Research Ethics since 2014. His research focuses on Active RC filters Nonlinear electronic circuits Analog integrated circuit design Network synthesis . His recent publications emphasize machine learning applications in RF/microwave design , quantum computing for CAD tools , and emerging memory devices . The department's Devreler ve Sistemler Laboratuvarı Çok Geniş Ölçekli Tümdevre (VLSI) Tasarımı Laboratuvarı likely support his work. Despite no explicit awards listed, his 15+ recent articles in high-impact journals underscore his technical contributions.
Dr. Emre Sefer is an Associate Professor at the Faculty of Engineering, Özyeğin University, specializing in machine learning and bioinformatics. He holds a Ph.D. in Computational Biology from Carnegie Mellon University (2015), an M.S. in Computer Science from University of Maryland College Park (2011), and a B.S. in Computer Engineering from Boğaziçi University (2008). His research bridges graph machine learning with financial networks, bioinformatics, and data engineering. Ph.D.: Computational Biology, Carnegie Mellon University M.S.: Computer Science, University of Maryland College Park B.S.: Computer Engineering, Boğaziçi University Research focuses on applying machine learning to financial and biological networks: Bioinformatics : 3D genome modeling, protein modifications, transcriptomic analysis Graph Machine Learning : GNNs for fraud detection, drug response prediction, and network evolution Financial Networks : Cryptocurrency investment strategies, asset price prediction His lab (OzU Machine Learning in Finance and Bioinformatics Lab) develops graph-based deep learning methods for cross-domain applications, including NFT market analysis and chromatin structure prediction. He received the Best research paper award at Recomb 2016 for work on 3D genome architecture. Former postdoc at CMU Machine Learning Department Industry experience as Quantitative Strategist at Goldman Sachs and JPMorgan
Mustafa Ünel is a Professor and Program Coordinator for Mechatronics Engineering at Sabanci University's Faculty of Engineering and Natural Sciences. He directs the Control, Vision and Robotics Research Lab and serves as a Senior Researcher at SU-IMC. His research spans robotics, computer vision, and machine learning applications in industrial systems. He earned a PhD in Electrical Engineering from Brown University and has held academic positions at Gebze Institute of Technology and Yale University. Current research projects include autonomous vehicle navigation, system health prediction, and aerospace manufacturing technologies funded by TUBITAK and Ford Otosan. He has supervised over 50 graduate theses and teaches courses including Autonomous Mobile Robotics, Nonlinear Control, and Computer Vision. His industrial collaborations focus on AI applications in automotive systems and construction automation.
Prof. Dr. Mehmet Reşit Tolun is a full-time Professor in the Department of Software Engineering at Çankaya University (Turkey) since 2022. Previously held full-time professor positions at Konya Food and Agriculture University (2020-2022), Aksaray University (2013-2017), and TED University (2011-2013), along with a part-time professorship at Başkent University (2017-2020). Specializes in Artificial Intelligence , Machine Learning , and Data Mining , with a focus on deep learning applications in aerospace, biomedical data analysis, and software process improvement. PhD in Computer Science (University of Kent, 1985) MSc in Computer Science (University of Kent, 1982) BSc in Physics and Computer Science (University of Kent, 1981) Research Interests span deep learning frameworks, hybrid expert systems, software engineering methodologies, and biomedical signal processing. Publications emphasize practical implementations in medical diagnostics, robotics, and agricultural pest detection. Scientific Awards include the IEEE Third Millenium Medal (2000). Supervised over 55 graduate students, including Burak Çetin, Uğur Özotuk, and Mahinur Doğan. Collaborated with researchers from Orta Doğu Teknik Üniversitesi , Çankaya University , and Aksaray University .