Biography

Chi Zhang is currently pursuing her PhD degree with the Department of Computer Science and Engineering, University of Gothenburg. She is a Marie Curie Early Stage Researcher within SHAPE-IT project, and a Wallenberg AI, Autonomous Systems and Software Program (WASP) affiliated PhD student.

Her research interests include applying deep learning and machine learing algorithms to pedestrian behavior prediction, and investigating interactions between pedestrians and vehicles/automated vehicles. She is under the supervision of Prof. Christian Berger and Prof. Marco Dozza.

From 2017 to 2020, she was an Senior R&D Engineer at the Intelligence Driving Group, Baidu, Beijing, China, in the area of automated driving perception. She received her BEng and MEng degrees in the Department of Control Science and Engineering from Zhejiang University, China, in 2014 and 2017, respectively.

Interests
  • Behavior Prediction
  • Deep Learning
  • Machine Learning
  • Computer Vision
  • Time Series Analysis
  • Intelligent Vehicles
Education

  • PhD in Computer Science and Engineering, From 2020 to present

    University of Gothenburg, Sweden

  • MEng in Control Engineering, 2017

    Zhejiang University, China

  • BEng in Automation, 2014

    Zhejiang University, China

Experience

 
 
 
 
 
University of Gothenburg
PhD Student
University of Gothenburg
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:

  • Predicting pedestrian trajectories
  • Predicting pedestrian intentions
  • Predicting and analyzing pedestrian-vehicle interactions
 
 
 
 
 
Baidu
Senior Software R&D Engineer
Baidu
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
Alibaba Group
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.

Projects

Supporting the Interaction of Humans and Automated Vehicles: Preparing for the Environment of Tomorrow (SHAPE-IT)
SHAPE-IT is a Innovative Training Network (ITN) project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement 860410. Chi is ESR3 of SHAPE-IT project.
Supporting the Interaction of Humans and Automated Vehicles: Preparing for the Environment of Tomorrow (SHAPE-IT)
Wallenberg AI, Autonomous Systems and Software Program (WASP)
WASP is a major national initiative for strategically motivated basic research, education and faculty recruitment. It is by far the largest individual research program in Sweden. Chi is an affiliated PhD student of WASP AI track.
Wallenberg AI, Autonomous Systems and Software Program (WASP)

Recent Publications

Chi Zhang, Janis Sprenger, Zhongjun Ni, Christian Berger (2024). Predicting and Analyzing Pedestrian Crossing Behavior at Unsignalized Crossings. In IEEE Intelligent Vehicles Symposium (IV) 2024.

PDF Cite Dataset

Chi Zhang, Zhongjun Ni, Christian Berger (2023). Spatial-Temporal-Spectral LSTM: A Transferable Model for Pedestrian Trajectory Prediction. IEEE Transactions on Intelligent Vehicles.

PDF Cite Dataset DOI

Chi Zhang, Christian Berger (2023). Pedestrian Behavior Prediction Using Deep Learning Methods for Urban Scenarios: A Review. IEEE Transactions on Intelligent Transportation Systems.

PDF Cite DOI

Chi Zhang, Amir Hossein Kalantari, Yue Yang, Zhongjun Ni, Gustav Markkula, Natasha Merat, Christian Berger (2023). Cross or Wait? Predicting Pedestrian Interaction Outcomes at Unsignalized Crossings. In IEEE Intelligent Vehicles Symposium (IV) 2023.

PDF Cite Poster DOI

Zhongjun Ni, Chi Zhang, Magnus Karlsson, Shaofang Gong (2023). A study of deep learning-based multi-horizon building energy forecasting. Energy & Buildings.

PDF Cite DOI

Zhongjun Ni, Chi Zhang, Magnus Karlsson, Shaofang Gong (2023). Leveraging Deep Learning and Digital Twins to Improve Energy Performance of Buildings. In IEEE IESES 2023.

PDF Cite DOI

Chi Zhang, Christian Berger (2022). Learning the Pedestrian-Vehicle Interaction for Pedestrian Trajectory Prediction. In IEEE ICCAR 2022.

PDF Cite Dataset DOI

Chi Zhang, Christian Berger (2022). Analyzing Factors Influencing Pedestrian Behavior in Urban Traffic Scenarios Using Deep Learning. Transport Research Arena (TRA) 2022.

PDF Cite DOI

Chi Zhang, Christian Berger, Marco Dozza (2021). Social-IWSTCNN: A Social Interaction-Weighted Spatio- Temporal Convolutional Neural Network for Pedestrian Trajectory Prediction in Urban Traffic Scenarios. In IEEE Intelligent Vehicles Symposium (IV) 2021.

PDF Cite Dataset Poster DOI

Chi Zhang, Christian Berger, Marco Dozza (2020). The Prediction of Pedestrian Behavior from LiDAR Data. L3Pilot Summer School 2020.

Cite Poster

Chi Zhang, Christian Berger, Marco Dozza (2020). Towards understanding pedestrian behavior patterns from LiDAR Data. In SAIS workshop 2020.

PDF Cite

Achievements

  • Sweden University Challenge Huawei Hackathon 2023, 1st place out of 170+ participants from Nordic universities with 6000 EUR prize, 2023.
  • Sweden University Challenge Huawei Hackathon 2022, 3rd place out of 200+ participants with 10,000 SEK prize, 2022.
  • 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.
  • Best New Employee, Perception Team, Baidu, 2017.
  • Outstanding Graduates of Zhejiang University & Zhejiang Province (top 5%), China, 2017.
  • Tianchi Data Contest: Cainiao demand forecasting and warehouse planning. Rank: top 3%, 2016.

Contact