I'm Sheng Zhong.
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As a Ph.D. candidate under the mentorship of Dr. Abdullah Mueen, my research focusing on: 1) Developing efficient and robust data mining and machine learning algorithms for analyzing real-time data. 2) Mining large temporal data sets for motif discovery, pattern recognition, and anomaly detection. 3) Developing semi-supervised and unsupervised ML & DL models. 4) Building real-time streaming data pipelines for data analysis and visualization. 5) Analyzing Blockchain data (Bitcoin & Ethereum). These skills have been applied across various domains, including seismic sensing, optical fiber monitoring, and blockchain analytics. Throughout my research journey, my primary goal is to address real-world challenges with innovative and cutting-edge solutions. Check out our projects.
**Sheng Zhong**, Vinicius M.A. Souza, Glenn Eli Baker, and Abdullah Mueen. 2023. Online Few-Shot Time Series Classification for Aftershock Detection. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23). Association for Computing Machinery, New York, NY, USA, 5707–5716. [<https://doi.org/10.1145/3580305.3599879>](<https://doi.org/10.1145/3580305.3599879>)
KDD presentation @ Long Beach,CA 2023/08/10
Two minutes introduction animation
Two minutes introduction animation
Poster
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