Topic: Spatiotemporal Data Mining, Representation Learning, Trajectory Data Mining
This project applies representation learning to trajectory data to transform original features into high-level information, improving the performance of downstream tasks such as travel time and destination prediction.
My major contributions include:
- I was the leader of this project and independently wrote and applied for the project. I also mentored two Master’s students (Wenchuang Peng and Yuan Wei).
- I developed a trajectory representation learning method and a travel time estimation model to enhance the accuracy of traffic-related tasks. The relevant research results are published in DOT and MMTEC.