Chi Zhang is currently pursuing her PhD degree under the supervision of Prof. Christian Berger and Prof. Marco Dozza with the Department of Computer Science and Engineering, University of Gothenburg. She received her BEng and MEng degrees in the Department of Control Science and Engineering from Zhejiang University, China, in 2014 and 2017, respectively. From 2017 to 2020, she was an engineer at the Intelligence Driving Group, Baidu, Beijing, China, in the area of automated driving perception.

Her research interests include applying deep learning to pedestrian behavior prediction, and investigating interactions between pedestrians and vehicles/automated vehicles.

  • Automated Driving
  • Computer Vision
  • Deep Learning
  • Artificial Intelligence
  • PhD in Computer Science and Engineering, Ongoing

    University of Gothenburg, Sweden

  • MEng in Control Engineering, 2017

    Zhejiang University, China

  • BEng in Automation, 2014

    Zhejiang University, China


University of Gothenburg
PhD Student
Feb 2020 – Present Gothenburg, Sweden

Project: the European project SHAPE-IT (Supporting the Interaction of Humans and Automated Vehicles: Preparing for the Environment of Tomorrow), funded by Marie Skłodowska-Curie Actions (MSCA) program.

Affiliated Ph.D. student of Wallenberg AI, Autonomous Systems and Software Program (WASP-AI) program.

Studies include:

  • Social Interaction Weighted Network for Pedestrian Trajectory Prediction in Urban Traffic Scenarios
  • Learning the Pedestrian-Vehicle Interaction for Pedestrian Trajectory Prediction
Senior Software R&D Engineer
Apr 2017 – Feb 2020 Beijing, China

Worked at Technology Department of Autonomous Driving (SAE Level 4), Intelligent Driving Group. Mainly dealt with the perception (detection and classification) of LiDAR point clouds data.

Projects include:

  • Multi-classification of objects from LiDAR data (3D point clouds) using deep learning algorithms.
  • Improvement of segmentation and data-driven detection from LiDAR data.
  • Research and development of filtering the false positive objects using machine learning methods.
Alibaba Group
Intern Software R&D Engineer
Jun 2016 – Sep 2016 Hangzhou, China

Worked at Technology Department of Cainiao Logistics and Supply Chain.

Project: Dealt with warehouse sales forecasting and replenishment optimization algorithm Forecasted sales for daily replenishment by time series method and machine learning methods.

Recent Publications

(2022). Pedestrian Behavior Prediction Using Deep Learning Methods for Urban Scenarios: A Review. In submission to IEEE Transactions on Intelligent Transportation Systems.

(2020). The Prediction of Pedestrian Behavior from LiDAR Data. L3Pilot Summer School 2020.

Cite Poster

(2020). Towards understanding pedestrian behavior patterns from LiDAR Data. In SAIS 2020.

PDF Cite


  • Sweden University Challenge Huawei Hackathon 2021, 3rd place out of 200+ participants with 10,000 SEK prize, 2021.
  • Outstanding employee of the quarter, Baidu, 2018.
  • Outstanding Graduates of Zhejiang University & Zhejiang Province (top 5%), China, 2017.
  • Tianchi Data Contest: Cainiao demand forecasting and warehouse planning. Rank: top 3%, 2016.