Recruiting M.S./Ph.D. students​ in deep learning & data mining. Require solid math, coding, and English reading. Value diligence, integrity, teamwork. Experience preferred.

中南大学
Visits:

Sinro Liu

Ph.D. Supervisor and Master's Supervisor

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  • Name:  Sinro Liu

  • Professional Title:  Associate Professor

  • Name (Pinyin):  liuxinru

  • Sex:  Male

  • School/Department:  School of Mathematics and Statistics

  • Education Level:  PhD Graduate

  • Date of Employment:  2011-07-05

  • Degree:  Doctoral degree

  • Alma Mater:  Central South University

  • Status:  Employed

  • Discipline:  Statistics. Mathematics

  • Enrollment Disciplines:  Mathematics、Statistics

  • Postal Address

  • Email

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Current Location: Home > team

Name of Research Group:
Time Series Intelligent Computing Group
Description of Research Group:
What we do.​ We address fundamental problems in time series modeling, forecasting, and decision-making — long-range dependency, non-stationarity, multi-scale coupling, and uncertainty quantification — by integrating geometric computing and analysis, deep learning, and data mining on a solid foundation of applied mathematics and statistics. Our research spans meteorological forecasting and diagnostic attribution, time series forecasting, chip optimization and simulation, and transportation big data analytics.

What we have achieved.​ The group maintains close collaboration with the Chinese Academy of Meteorological Sciences and the climate centers of Guangdong, Chongqing, Hubei, and Sichuan (Southwest Region). Several systems developed by the group have been deployed in operational use, including the ensemble forecasting system for high-impact marine climate events in the South China Sea, the Guangdong intelligent forecasting system, and the extended-range air quality forecasting system, as well as simulation software for optimizing flip-chip interconnect parallelism. The group has published over 40 papers in journals including BAMS, AAS, QJRMS, Computer-Aided Design, and Knowledge-Based Systems.

Join us.​ Students with backgrounds in mathematics, statistics, computer science, or atmospheric sciences are welcome.

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