My Blog Recent Publications
Research & Contributions (Updated: February 2025)
My work focuses on advancing AI through research in graph neural networks, deep learning,
and intelligent transportation systems. With multiple publications and growing citations,
I strive to push the boundaries of AI applications, contributing to both academia and industry.
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Published in IEEE Transactions ON Intelligent Transportation Systems, 2023.
In this survey, we provide an overview of GNN studies in the general domain of ITS. We explore how GNN
frameworks have evolved for different ITS applications, including
traffic forecasting, demand prediction, autonomous vehicles,
intersection management, parking management, urban planning,
and transportation safety.
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Published in 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC).
In this study, we propose Multi-Component Spatial Temporal Graph Attention Convolution Neural Network (Multi-STGAC), a graph deep learning model to predict short-term bus passenger flow. It incorporates a Graph Attention Network and a Graph Convolution Neural Network to consider spatial correlations in bus network data.
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Published in Transportation Research Record: Journal of the Transportation Research Board.
This paper develops a bus network graph convolutional long short-term memory (BNG-ConvLSTM) neural network model to forecast short-term passenger flows in bus networks.
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