About Me

I am currently a Ph.D. student under the supervision of Prof. Karine Zeitouni and Dr. Yehia Taher, with Ambient Data Accessing and Mining team of DAVID Lab, UVSQ, Université Paris-Saclay. I received my B.Sc degree in Optical & Electronic Information from Huazhong University of Science & Technology, China in 2015, and my M.Sc. degree in Data Science from UVSQ and University of Paris-Saclay, France in 2018, as well as an engineer degree in Computer Science from Polytech Sorbonne & Sorbonne Université, France in 2017. My research interests include Time Series analytics, Data stream mining, and Spatio-Temporal data analysis, with applications on advanced machine learning techniques.

Curriculum vitae

Here is my CV (short), CV (long).

⭐️⭐️I am currently on the job market, thank you for any proposals. ⭐️⭐️

Journals:

• J. Zuo, K. Zeitouni, Y. Taher, S. G. Rodriguez: “Graph Convolutional Networks for Traffic Forecasting with Missing Values”, accepted by Data Mining and Knowledge Discovery (DMKD), Springer
• H. El Hafyani, M. Abboud, J. Zuo, K. Zeitouni and Y. Taher: “Learning the Micro-environment from Rich Trajectories in the context of Mobile Crowd Sensing - Application to Air Quality Monitoring”, to appear in GeoInformatica, Springer (2022)

International Conferences & Workshops:

• J. Zuo, K. Zeitouni and Y. Taher: “SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series”, 2021 IEEE International Conference on Data Mining (ICDM’21). preprint, full version, code, slides
• H. El Hafyani, M. Abboud, J. Zuo, K. Zeitouni and Y. Taher: “Tell Me What Air You Breath, I Tell You Where You Are”, (demo) 2021 International Symposium on Spatial and Temporal Databases (SSTD’21)
• M. Abboud, H. El Hafyani, J. Zuo, K. Zeitouni and Y. Taher: “Micro-environment Recognition in the context of Environmental Crowdsensing”, in Big Mobility Data Analytics with EDBT 2021 (BMDA’21)
• J. Zuo, K. Zeitouni and Y. Taher: “Incremental and Adaptive Feature Exploration over Time Series Stream”. (regular paper) 2019 IEEE International Conference on Big Data (BigData’19), Los Angeles, CA, USA, 2019. preprint, code, slides
• J. Zuo, K. Zeitouni and Y. Taher: “ISETS: Incremental Shapelet Extraction from Time Series Stream“，(demo) 2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’19), Würzburg, Germany, 2019. poster, preprint, code
• J. Zuo, K. Zeitouni and Y. Taher. “Exploring Interpretable Features for Large Time Series with SE4TeC”, (demo) 22nd International Conference on Extending Database Technology (EDBT’19), Lisbon, Portugal, 2019. poster, preprint, code

National Conference:

• J. Zuo, K. Zeitouni and Y. Taher. “Time Series meet Data Streams: Perspectives of the Interdisciplinary Collision and Applications”, PhD symposium, 35ème Conférence sur la Gestion de Données – Principes, Technologies et Applications (BDA’19), Lyon, France, 2019.

Organizing committees:

• MDM 2020 Web Chair of the 21st IEEE Mobile Data Management Conference
• JDSE 2019 Junior organization committee of the 4th Paris-Saclay Junior Conference on Data Science and Engineering

Program committees:

• ECML-PKDD 2020 The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Reviewing:

• SIGSPATIAL 2022 ACM International Conference on Advances in Geographic Information Systems

• ICDE 2021 IEEE International Conference on Data Engineering

• AAAI 2021 AAAI Conference on Artificial Intelligence

• SSTD 2021 International Symposium on Spatial and Temporal Databases

• DSAA 2020 IEEE International Conference on Data Science and Advanced Analytics

PROJECT STREAMOPS - INSTITUT DATAIA

• Open Source Platform for Research and Integration of Algorithms for Massive Time Series Flow Analysis
• The goal of StreamOps is to develop methods and algorithms to consider temporal order in data streams.

• jingwei.zuo@uvsq.fr
• (+33)06 50 13 98 29
• Office D-317A, Building Descartes, UVSQ, 45 avenue des Etat-Unis, 78000, Versailles, France