Bio

Jingwei Zuo is a first-year 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 distributed algorithm 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, France in 2017.

Conference:

• J. Zuo, K. Zeitouni and Y. Taher: “Incremental and Adaptive Feature Exploration over Time Series Stream”. (Accepted) 4th Workshop on Advanced Analytics and Learning on Temporal Data (AALTD@ECML-PKDD’19), Würzburg, Germany, 2019
• J. Zuo, K. Zeitouni and Y. Taher: “ISETS: Incremental Shapelet Extraction from Time Series Stream”. (Accepted) demo paper, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’19), Würzburg, Germany, 2019
• J. Zuo, K. Zeitouni and Y. Taher. “Exploring Interpretable Features for Large Time Series with SE4TeC”, demo paper, 22nd International Conference on Extending Database Technology (EDBT’19), Lisbon, Portugal, 2019. [Poster]

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-312B, Building Descartes, 45 avenue des Etat-Unis, 78000, Versailles, France