Vedat Toğan

Vedat ToğanVedat Toğan is a distinguished Professor of Civil Engineering at Karadeniz Technical University (KTU) with a profound expertise in the integration of artificial intelligence (AI) and machine learning (ML) in civil engineering. His academic tenure began at KTU, where he pursued his undergraduate and graduate studies in civil engineering, culminating in a Ph.D. With international academic exposure at Germany's Ruhr University of Bochum and the Netherlands' Delft University of Technology on prestigious TUBITAK scholarships, Dr. Toğan has garnered a unique global perspective that enriches his research. As a seasoned author, his work is published in several high-impact journals and books, advancing knowledge in the AI-enhanced civil engineering sector. In his professorial role, Dr. Toğan developed several multi-objective optimization approaches and the application of advanced machine learning models for predictive analytics in construction project management. His scholarly contributions include extensive research on the utilization of graph convolutional networks for enhancing construction safety, quality, and productivity and deploying deep learning for structural analysis and cost prediction in buildings. Dr. Toğan's notable publications include studies on construction safety using graph convolutional networks, deep neural networks for structural calibration, and machine learning systems for accident severity prediction. His latest work involves cutting-edge explorations into graph representation learning for construction defects, large language models for construction safety, and emotionally intelligent machine learning. Dr. Toğan's scholarly output also includes influential books and book chapters, like his recent contribution to "Artificial Intelligence and Machine Learning Techniques for Civil Engineering".

Publications

Explainable Safety Risk Management in Construction With Unsupervised Learning
Explainable Safety Risk Management in Construction With Unsupervised Learning
Fatemeh Mostofi, Vedat Toğan. © 2023. 33 pages.
The success of Machine Learning (ML) approaches as promising solutions has encouraged their widespread implementation across different fields. Owing to the high accident rate...