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NAME:Weizhu QIAN

Career:Lecturer

Organization:School of Computer Science and Technology

Degree:PhD

Graduate School:Université Bourgogne Franche-Comté (France)

Email:wzqian(at)suda(dot)edu(dot)cn

Office Location:

Tel:

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Biography

  • Organization:School of Computer Science and Technology
  • Tel:
  • Gender:male
  • Email:wzqian(at)suda(dot)edu(dot)cn
  • Post:
  • Office Location:
  • Graduate School:Université Bourgogne Franche-Comté (France)
  • Address:333 Ganjiangdong Road, Suzhou, Jiangsu, China
  • Degree:PhD
  • PostCode:215008
  • Academic Credentials:
  • Fax:

Education

Education:
BS: Northwestern Polytechnical University (China)          09/2010 ~ 07/2014
MS: University of Chinese Academy of Sciences (China) 09/2014 ~ 01/2017
PhD: Université Bourgogne-Franche-Comté (France)       10/2017 ~ 02/2021


Professional Experiences

Work Experience:

Lecturer,  Soochow University (China),   08/2023 - current

Postdoc,  Aalborg University (Denmark),   04/2021 - 04/2023


Overview

Resume:

Hi! I'm a Lecturer (Assistant Professor) at the School of Computer Science and Technology, Soochow University, China. My research interests mainly focus on deep learning and data science. More specifically, I am into statistical deep learning methods (e.g., variational inference, generative modelling, uncertainty quantification, SDEs, and optimal transport) and its applications to time series analysis. As a researcher, I'm fascinated by the elegance of theortitical foundation of modern deep learning, and enjoy discussing scientific problem with others. So if you are also interested thoses research topics, feel free to contact me.        


Professional Service

Social Position:

Research

Research Field:

Deep Learning,  Probabilistic Infernece, Data Science, Uncertainty Quantification, Time Series Analysis

Teaching

Open Course:

2023 Fall: Comprehensive Project Pratice (a project-based course focused on data science and machine learning).

Projects

Research Project:

Publications

Thesis:
Weizhu Qian, Yan Zhao, Dalin Zhang, Bowei Chen, Kai Zheng, Xiaofang Zhou. Towards  
A Unified Understanding of Uncertainty Quantification in Traffic Flow Forecasting. (IEEE  

Transactions on Knowledge and Data Engineering, 2023).

Weizhu Qian, Dalin Zhang, Yan Zhao, Kai Zheng, James J.Q. Yu. Uncertainty Quantifica
tion for Traffic Forecasting: A Unified Approach (39th IEEE International Conference on  
Data Engineering, ICDE 2023).
Weizhu Qian, Fabrice Lauri, Franck Gechter. Supervised and Semi-supervised Deep  
Probabilistic Models for Indoor Positioning Problems. (Neurocomputing 2021, 435, 228-238).


Books&Patents

Books Writings: Patents Patent:

Honors

Honor Reward:

Supervision

Enrollment: