- Data Mining
- Web Mining
- Recommendation Systems
- +۱۲ مورد دیگر
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.
