Bio

Jingwei Zuo is 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(Donnée et Algorithmes pour une Ville Intelligente et Durable), UVSQ, Université Paris-Saclay. His research interests include Time Series analytics, Data Streams mining and Spatio-Temporal data analysis in the context of IoT. He received his B.Sc degree in Optical & Electronic Information from Huazhong University of Science & Technology, China in 2015, and his M.Sc. degree in Big Data from UVSQ and University of Paris-Saclay, France in 2018, as well as an engineer degree in Electronic & Computer Science from Polytech Sorbonne & Sorbonne Université, France in 2017.

International Conference & Workshop:

• J. Zuo, K. Zeitouni and Y. Taher: “SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series”, to appear. 2021 IEEE International Conference on Data Mining (ICDM’21). preprint, GitHub
• 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
• 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
• 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]

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:

• 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