Yancheng Ling - PostDoc at KTH

About Me

I am currently a Postdoctoral Researcher specializing in transporation knowledge graphs and autonomous driving at KTH Royal Institute of Technology. I completed my PhD in Transportation from the South China University of Technology in 2024 . My research interests include environmental perception for autonomous driving and integrating LLMs for transporation knowledge graphs.

Education

• South China University of Technology
  PhD, Traffic Information Engineering and Control(2019–2024)

• Kungliga Tekniska högskolan
  Visiting PHD, Transporation Science(2022-2023)

• South China University of Technology
  Master, Transportation Engineering (2017–2019)

• East China Jiaotong University
  Bachelor, Transportation Engineering and Internet of Things Engineering(2013-2017)

Selected Papers

PedAST-GCN: Fast pedestrian crossing intention prediction using spatial–temporal attention graph convolution networks

Y Ling, Z Ma, Q Zhang, B Xie, X Weng(2024), IEEE Transactions on Intelligent Transportation Systems
📄 Paper

SA-BiGCN: Bi-stream graph convolution networks with spatial attentions for the eye contact detection in the wild

Y Ling,Z Ma, B Xie, Q Zhang, X Weng. (2023), IEEE Transactions on Intelligent Transportation Systems
📄 Paper

LVLMPed-CoT: A Large Vision-Language Model with Chain-of-Thought Mechanism for Pedestrian Crossing Intention Prediction

Y Ling,Z Ma, ect. (2025), Under Review

A review of knowledge graph construction using large language models in transportation: problems, methods, and challenges

Y Ling,Z Ma, etc. (2025), Transportation Research Part C: Emerging Technologies
📄 Paper

A deep learning approach for robust traffic accident information extraction from online chinese news

Y Ling, Z Ma, X Dong, X Weng. (2024), IET Intelligent Transport Systems
📄 Paper

Bus driver deceleration behavior modeling at intersections using multi-source on-board sensor data

Y Ling, Z Ma, Y Song, Q Zhang, X Weng, X Ma. (2025), Journal of Public Transportation
📄 Paper

Efficient and Robust Driver Fatigue Detection Framework Based on the Visual Analysis of Eye States

Y Ling X Weng. (2023), Promet - Traffic&Transportation
📄 Paper

Driver eye location and state estimation based on a robust model and data augmentation

Y Ling R Luo, X Dong, X Weng (2023), IEEE Access
📄 Paper

For a full and up-to-date list of my publications: Google Scholar profile.

Experience

• Postdoc at KTH
  (Full-time), 2024– LLMs for Transportation Knowledge Graphs and Autonomous Driving

• Teaching Assistant

  • AH2179 HT25 Applied Artificial Intelligence in Transportation(2025): led practice classes on LLMs and NLP (Python/PyTorch/TensorFlow), graded assignments and exams.

Research Interests

• Large Language Models (LLMs)
• Autonomous Driving
• Transporation knowledge graph

Find Me Online

• GitHub
• Google Scholar

Thank you for visiting my academic website!