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Digital Roads of the Future

 

Name: Rui Kang

Academic Division: Civil Engineering

Research Group: Construction Engineering – Digital Roads  

Email:  rk703@cam.ac.uk 

Research Interests

Rui’s research interests mainly lie in digitalisation for road maintenance process, including road maintenance recipe automatic generation, automated planning for on-site work and ontology database in infrastructure. Her research focuses on digital twin-based management during the maintenance stage and aims to fully automate the process from management to execution through collaboration with National Highways.  

Strategic Themes

  • Establish infrastructure ontology database for the use of real-world management. 
  • Design nondeterministic planning from knowledge graph and reasoning methods. 
  • Carry out decision making and output human/machine readable recipes for maintenance tasks.  

Research Project

Digital Roads of the Future (DRF) initiative. The research encompasses four key areas, exploring how they can work together to develop a connected physical and digital road infrastructure system, while being underpinned by sustainability, to help reduce traffic, reduce greenhouse gas emissions, and electrify the network. For more:  https://drf.eng.cam.ac.uk/research 

Rui is working with the Data Science group and in charge of Process Guidance Generation related research. 

Biography

Rui received her master’s degree (2022) in School of Civil Engineering at Southeast University in China. Her master’s thesis is about apply digitalisation in large scale foundation pit for structure health monitoring. This thesis involves in point cloud processing, management through BIM platform and elements classification based on Deep Learning. Before that, she majored in project management especially for construction and mainly focused on BIM technologies. 

For now, Rui is a PhD student at University of Cambridge, working with Digital Roads of the Future (DRF) research group. She is researching on road maintenance field and exploring a more applicable method to automate decision making and on-site work guiding.