Prof. Vilda Purutçuoğlu is a Professor in the Department of Statistics at Middle East Technical University (METU). Her academic career includes roles as Assistant Professor (2010–2012), Associate Professor (2012–2018), and Professor since 2018. She holds a Ph.D. from Lancaster University (2007) and has affiliations with the Department of Biomedical Engineering, Institute of Applied Mathematics, and Informatics Institute at METU. Her research focuses on bioinformatics, systems biology, high-dimensional data analysis, neuroscience, and social statistics . Key professional roles include Head of the Department of Statistics (since 2025), Chair of the Award Fund Committee at the International Biometric Society (since 2022), and Editorial roles in journals like BMC Bioinformatics. She has led projects on topics ranging from family dynamics to outlier detection in biomedical data, funded by TÜBİTAK and METU. Prof. Purutçuoğlu has been recognized with multiple Academic Performance Awards (2011–2022 excluding 2020) and was a finalist for the Sabri Ülker Science Award (2015). She collaborates internationally, including a Global Engagement Fellowship (2024–2025) at University College London and research at Università Della Svizzera Italiana (2024). Her publications span books on operations research and bioinformatics, and she actively supervises projects and students in interdisciplinary areas like biomedical engineering and computational statistics.
Ismail Rakip Karas is a Professor of Computer Engineering and Head of the 3D GeoInformatics Research Group at Karabuk University, Turkey. He holds a BSc from Selcuk University (1997), MSc from Gebze Institute of Technology (2001), and PhD from Yildiz Technical University (2007). His career includes roles as Visiting Researcher at Universiti Teknologi Malaysia (2010–2014) and Research Assistant at Gebze Institute of Technology (2000–2009). Currently, he serves as Deputy Rector of Karabuk University and has held administrative positions including Dean of Safranbolu Fine Art and Design Faculty, Director of Safranbolu Vocational School, and acting Dean of the Faculty of Architecture. Research interests span GeoInformatics, 3D GIS, network analysis, spatial data structures, and intelligent transportation systems. He has led over 20 national/international projects, including EU-funded initiatives and collaborations with institutions like Nara Institute of Science and Technology and University of Szeged. His work emphasizes smart city applications, indoor navigation, and emergency evacuation models. Publications include over 100 peer-reviewed articles and book chapters, focusing on GIS applications, machine learning in geospatial analysis, and 3D modeling. He has organized conferences like Geo-Advances 2017 and serves on editorial boards of journals such as the International Journal of Geo-Spatial Knowledge and Intelligence.
Övgü Öztürk Ergün is an Assistant Professor in the Department of Software Engineering at Muğla Sıtkı Koçman University's Faculty of Engineering. She holds a Ph.D. from The University of Tokyo's Department of Frontier Informatics. Her research focuses on computer vision, machine learning, and AI applications in areas such as augmented reality, cultural heritage digitization, and human behavior analysis. She has led multiple TÜBİTAK-funded projects including 'Customer Tracking and Interest Measurement Technologies for Retail Sector Sales Performance Improvement' and '3D Modeling of Cultural Heritage Sites.' Her work spans academic publications, industry collaborations, and innovative teaching in software engineering and interactive multimedia systems. Education: Middle East Technical University, B.Sc. Electrical & Computer Engineering (2003) University of Tokyo, Ph.D. Frontier Informatics (2010) Research Interests: Her interdisciplinary research integrates computer vision with real-world applications, including privacy-preserving biometrics, smart environment monitoring, and cultural heritage preservation. She has pioneered ontology-based systems for Turkish cuisine and developed AR tools for virtual try-on. Her work emphasizes ethical AI and context-aware systems, with recent focus on food recognition using CLIP models and churn prediction in telecom sectors. Awards & Grants: TÜBİTAK Undergraduate Software Projects Competition (2013) Robot Days 3rd Place (2013) Completed TÜBİTAK 1001/1505 projects totaling over 500k USD funding Advising & Labs: Supervised BENGÜ-ÖZTÜRK's thesis on food image recognition. Active in the University's Research & Application Centers for Computer Vision and AR/VR development. Collaborates with ISTKA and Ministry of Development on cultural heritage digitization projects.
Prof. Şule Öğüdücü is a full-time Professor in the Department of Artificial Intelligence and Data Engineering at Istanbul Technical University (ITU), Faculty of Computer and Informatics. She has been serving as the Department Chair since 2019 and has held various administrative roles including Associate Dean (2012–2015) and Faculty Board Member. Her academic journey began with a B.Sc. in Electronics and Communication Engineering from ITU, followed by an M.Sc. in Biomedical Engineering from Boğaziçi University, and a Ph.D. in Computer Engineering from ITU. During her doctoral studies, she was a Research Associate at the University of Waterloo’s Database Laboratory (2001–2003), supported by NSERC and Tinçel Foundation grants. B.Sc., Electronics and Communication Engineering, Istanbul Technical University, 1987–1991 M.Sc., Biomedical Engineering, Boğaziçi University, 1991–1995 Ph.D., Computer Engineering, Istanbul Technical University, 1999–2003 Her research is centered on data mining, web mining, recommendation systems, social network analysis, big data, community detection, and forecasting applications in finance and demand. She is recognized internationally, ranking 27th in Google Scholar in recommendation systems and 1st in Turkey. Her recent work emphasizes AI-driven solutions in network security, explainable AI, and industrial applications such as oil industry flash point prediction and e-commerce demand forecasting. The analysis of her recent publications (2022–2025) reveals a strong trend toward integrating deep learning and graph neural networks (GNNs) into recommendation and network anomaly detection systems. There is a growing focus on explainability (XAI), semi-supervised learning, and real-world applications in critical infrastructure (e.g., backbone networks, traffic, oil industry). Her work bridges theoretical AI advancements with practical implementations in cybersecurity, smart cities, and industrial automation. Her scientific honors include: Siemens Excellence Award, 2004 TÜBİTAK Threshold Award, 2024 Prof. Öğüdücü has led numerous research projects, including TÜBİTAK-funded initiatives and ITU Research Fund grants. She is the Principal Investigator (PI) of multiple ongoing projects such as 'Explainable AI Methods for Earthquake Prediction,' 'AI-Based Demand Forecasting for the Fashion Industry,' and 'Black Hole Anomaly Detection in Backbone Networks.' She also engages in sectoral collaborations with companies like Ericsson, KariyerNet, and IDEA Technology, providing academic consultancy in dynamic pricing, financial analysis, and real-time system scaling. She has supervised 33 academic works, reflecting her active role in mentoring students. Additionally, she founded the IEEE Turkey WIE Affinity Group in 2010, contributing significantly to the promotion of women in engineering. She leads research teams working on AI and data engineering applications, particularly in network security, recommendation systems, and industrial AI. Her labs focus on developing benchmark datasets (e.g., IBB Traffic Graph Data), predictive models, and explainable AI frameworks. Current teams are engaged in projects funded by TÜBİTAK and industry partners, emphasizing real-time, scalable, and interpretable AI solutions.
Müjdat Çetin is a Professor of Electrical and Computer Engineering and serves as the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and Director of the New York State Center of Excellence in Data Science at the University of Rochester. He previously held faculty positions at Sabancı University and was a Research Scientist at MIT, with visiting roles at Boston University, Northeastern University, and MIT. Education: PhD in Electrical Engineering, Boston University, 2001 MS in Electrical Engineering, University of Salford, 1995 BS in Electrical Engineering, Boğaziçi University, 1993 His research lies at the intersection of signal processing, machine learning, and data science, with applications in biomedical imaging, radar, and brain-computer interfaces. He develops probabilistic and deep learning models for robust information extraction from noisy and complex data. His work emphasizes computational imaging, sparse representations, and multimodal data fusion. The recent publications reflect a strong trend toward integrating Bayesian methods and deep learning in imaging sciences, particularly in medical image reconstruction, neuroimaging analysis, and radar systems. His group actively explores transformer architectures, federated learning, and model-based deep learning for solving inverse problems in imaging. Scientific Awards and Honors: IEEE Fellow IEEE Signal Processing Society Best Paper Award IET Radar, Sonar and Navigation Premium Award Elsevier Signal Processing Best Paper Award Turkish Academy of Sciences Distinguished Young Scientist Award (GEBİP) ODTÜ Mustafa Parlar Foundation Research Incentive Award TÜBİTAK Career Award Boston University Best Engineering Research Award Professor Cetin has advised numerous PhD and Master’s students and led significant research grants in data science and imaging. He has served as a Senior Area Editor for IEEE Transactions on Image Processing and IEEE Transactions on Computational Imaging, and held editorial roles in several top journals. He has chaired major conferences including ICASSP, ICIP, and IVMSP workshops. He leads a multidisciplinary research group focused on data science and imaging, collaborating with neuroscientists and medical researchers. The team develops novel algorithms for brain-computer interfaces, medical image analysis, and remote sensing systems, often integrating machine learning with physical models of data acquisition.
Birsen GÜLDEN ÖZDEMİR is an Assistant Professor in the Department of Computer Engineering at the Faculty of Engineering, Doğuş University, where she has been a faculty member since 2007 after serving as a research assistant at Middle East Technical University from 2000 to 2005. Her academic credentials include: PhD in Informatics, Middle East Technical University (2004), thesis: 'NetON: A new tool for discovering the semantic potential of biomedical data in UMLS semantic network' Master of Science in Informatics, Middle East Technical University (2000), thesis: 'A Geographical Information System Application for Ambulance Routing Services: A Prototype' Bachelor of Science in Engineering, Middle East Technical University (1999) Her research spans Semantic Web technologies, algorithm design, database systems, and software engineering, with practical applications in biomedical data semantics and geographical information systems. She teaches core courses including Database Design, Web Programming, Algorithms, and Software Engineering. Dr. Özdemir actively supervises graduate research, recently guiding Furkan Şentürk's 2024 Master's thesis on 'Hybrid graph neural networks for image matching'.
Ali Taylan Cemgil is an Associate Professor at Bogazici University's Department of Computer Engineering, College of Engineering. His research focuses on Bayesian statistics, machine learning, and audio/music processing within the Perceptual Intelligence Laboratory (PILAB). PhD in Computer Science from Radboud University Nijmegen (2004) Postdoctoral research at University of Amsterdam (Intelligent Autonomous Systems Lab) and University of Cambridge (Signal Processing and Communications Lab) Research Interests: Bayesian modeling and time series analysis Audio signal processing and source separation Human-AI collaboration frameworks Probabilistic methods in AI reliability and fairness Scientific Contributions: Recent work explores conformal prediction for model calibration, adversarial robustness in deep learning, and fairness-aware medical AI systems. His research spans theoretical foundations in Bayesian statistics and practical applications in indoor localization and capsule robotics. Academic Service: Current faculty member with extensive publications in AI/ML, signal processing, and probabilistic modeling.
Professor Ahmet Karadoğan is affiliated with the Faculty of Humanities and Social Sciences , specializing in Turkish language and literature. His academic career spans over two decades, with a focus on Turkish linguistics, historical syntax, and orthography studies. Research Themes : Turkish verb aspect, alphabet transitions, sociolinguistics, and computational modeling of social networks. Key Contributions : Bibliometric analysis of technology in language teaching, structural studies on Turkish suffixes, and historical Turkish manuscript analysis. Methodology Trends : Combines computational approaches (e.g., Petri nets) with traditional linguistic analysis, emphasizing interdisciplinary applications.
Cüneyd DEMİR is a full-time Lecturer at Ahi Evran University's Mucur Vocational School, Department of Computer Technologies. He has held this position since 2019 and was promoted to Doktor Öğretim Görevlisi (Lecturer with PhD) in 2024. His administrative roles include Department Head (2021-2023), Vice Director of the Vocational School (2021-present), and membership in university committees (Quality Board, Management Council). He holds a PhD in Industrial Design Engineering from Gazi University (2020-2024), an MSc in Defense Technologies from Kırıkkale University (2015-2017), an MSc in Occupational Health and Safety from Aksaray University (2019), and a BSc in Mechatronic Engineering from Gaziosmanpaşa University (2011-2015). His research focuses on Robotics , Mechatronic System Design , Computer-Aided Design/Manufacturing (CAD/CAM) , and Artificial Intelligence , with emphasis on unmanned ground vehicles (UGVs), defense systems, renewable energy integration, and AI-driven design methodologies. Publications primarily explore UGV design using machine learning, solar-powered autonomous systems, and material science for robotics. Recent works demonstrate strong trends in AI/neural network applications for defense technology and systematic design processes. He contributed to the TÜBA/TÜBİTAK-supported project: "Güneş Enerjisi İle Uçuş Süresi Artırılmış Otonom Model Uçak" (Solar-Powered Autonomous Model Aircraft with Extended Flight Duration, 2014-2015) as a researcher.
MUSTAFA OĞUZ NALBANT is a Lecturer at Manisa Celal Bayar University's Soma Vocational School , Department of Electronics and Automation. With a doctorate in Mechanical Engineering (2019-2022) and postgraduate/undergraduate degrees from Yildiz Technical University and Bayburt University, he focuses on vibration analysis in mechanical systems, biomedical device technology, and noise-induced health effects in mining environments. Education Doctorate (2019-2022), Manisa Celal Bayar University Postgraduate (2014-2016), Yildiz Technical University Undergraduate (2009-2013), Bayburt University His research spans Mechanical Engineering , Nanotechnology , and Occupational Health . Recent works include nonlinear vibration studies of stepped nanobeams using nonlocal elasticity theory, statistical analysis of noise exposure in underground mining, and dynamic modeling of elevator systems. His publications appear in journals like Zeitschrift für Naturforschung and Advances in Nano Research , with citations reflecting interdisciplinary impact. Notable trends in his publications include: Nonlocal elasticity modeling in nanostructures Noise pollution and physiological health effects Linear graph method for mechanical systems Projects include TUBITAK-funded science festivals and physiologic noise impact studies in mining sectors.
Özgür Özpeynirci is an Assistant Professor at the Department of Logistics Management, Izmir University of Economics, where he has been employed since February 2008. His research focuses on multiobjective decision making, combinatorial optimization, and scheduling, bridging theoretical and applied aspects of operations research and logistics. B.S., M.S., and Ph.D. in Industrial Engineering from Middle East Technical University (2002, 2004, 2008) Researcher at TÜBİTAK (2001-2007) His scholarly work integrates operations research, decision theory, and logistics. He has pioneered interactive algorithms for multi-criteria sorting and resource allocation, addressing complex problems in transportation, biofuel contracts, and digital transformation. His research often applies mathematical modeling and optimization techniques to real-world scenarios. Scientific awards include the 2011 Best Doctoral Dissertation Award from the International Society on Multiple Criteria Decision Making. His publications span high-impact journals like Management Science and European Journal of Operational Research , emphasizing algorithm design, logistics performance, and multiobjective programming. Co-authors like Vincent Mousseau and Selin Özpeynirci indicate collaborative research across Turkey and global institutions.
Hasan Sözer is a Professor at the Department of Computer Science , Ozyegin University , where he has worked since 2011. His research focuses on software engineering , particularly in software architecture recovery , fault tolerance , and distributed systems . Education: B.Sc. in Computer Engineering , Bilkent University (2002) M.Sc. in Computer Engineering , Bilkent University (2004) Ph.D. in Computer Science , University of Twente (2009) Research Interests include software architecture design , test automation , and self-adaptive systems . His work often combines genetic algorithms and heuristics for architecture recovery, with applications in blockchain security and embedded systems . Scientific Projects funded by the Scientific and Technological Research Council of Turkey include topics like automated web application testing , blockchain-based security solutions , and serverless function deployment . He collaborates with industry partners such as Turkcell Technology , Vestel , and Fibabanka . Students under his supervision include Hüseyin Yapıcı , who defended a thesis on evolutionary coupling metrics . He leads the Ozyegin University Software Research Lab (SRL) , which focuses on modular architecture recovery and test model refinement .
Aissa Houdjedj is a Researcher in the Department of Computer Engineering at Antalya Bilim University (Antalya, Turkey) and a Ph.D. candidate in Computer Engineering at Akdeniz University. His roles include contributing to TÜBİTAK research projects in bioinformatics. Doctorate: Akdeniz University Master's: Antalya Bilim Üniversitesi Bachelor's: Antalya Bilim Üniversitesi His research focuses on: Bioinformatics Algorithms Computational Analysis of Biological Networks Design Machine Learning Artificial Intelligence Graph Algorithms Engineering
ENİS ARSLAN is an Assistant Professor at the Department of Computer Engineering, Faculty of Engineering, Çanakkale Onsekiz Mart University. His research spans Natural Language Processing, Image Processing, Artificial Intelligence, and Remote Sensing. Ph.D. in Computer Engineering from Çukurova University (2020) Master's in Computer and Information Sciences from Doğuş University (2013) Master's in Business Administration from Beykent University (2009) B.Sc. in Computer Engineering from Yıldız Technical University (2001) His work focuses on UAV-based 3D documentation of cultural heritage, flood mapping with machine learning, and Turkish morphological disambiguation. He has contributed to journals like ACM Transactions on Asian and Low-Resource Language Information Processing and Environmental Monitoring and Assessment . His projects include Tübitak-funded initiatives on smart tracking systems and UAV applications in geospatial analysis. He has taught courses in software development and computational linguistics.
Umut Akovalı is an Assistant Professor of Economics at Ozyegin University , Istanbul. He earned his Ph.D. (2014-2020) and M.A. (2010-2014) at Galatasaray University and Koç University, respectively, and holds a B.A. from Dokuz Eylül University (2005-2010). His research focuses on financial econometrics and network analysis , with applications to systemic risk, monetary policy, and pandemic economics. Education Ph.D., Koç University (2014-2020) M.A., Galatasaray University (2010-2014) B.A., Dokuz Eylül University (2005-2010) His working papers explore connectedness-driven risk in financial systems, Covid-19 network dynamics in U.S. states, and monetary policy impacts on bond markets. Current projects include VAR model identification via directed acyclical graphs and agent-based pandemic simulations. Research Trends Network risk modeling Crisis spillover analysis Pandemic-economic policy intersections Monetary-fiscal policy coordination He has professional experience as a Risk Management Specialist at Istanbul Stock Exchange Clearing Bank and teaches Econometrics , Money and Banking , and Introduction to Economics at undergraduate and graduate levels.
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