GISRUK’s Post

🚀 Thrilled to share my experience at #GISRUK2024 in Leeds! This year marked my fourth presentation at GISRUK, and as always, I received invaluable feedback that will greatly enhance my further studies. 📣 This year, I presented our latest work on "Missing Data Imputation for Traffic Accident Records: A Deep Learning Method." We developed a framework that effectively addresses complex scenarios of missing data in the #STATS19 dataset, UK, by transforming the imputation challenge into predicting edge values using Graph Representation Learning 🛠️. The outcomes have been promising and are a testament to the innovative approaches in deep learning for data-driven traffic accident research ✅. Immense gratitude to my supportive and insightful supervisors, James Haworth and Huanfa C., as well as my brilliant colleague from UCL SpaceTimeLab and UCL Dept of Civil, Environmental & Geomatic Engineering, Ilya Ilyankou, for their contributions to this research. It was also wonderful to reconnect with fellow GIS enthusiasts and researchers. Cheers 🥂 Looking forward to the Bristol next year~