This symposium is intended to give an opportunity for graduate students and young researchers of Waseda university to know the advanced research topics in the field of data analytics. In this symposium, Prof. Fugee Tsung, the Hong Kong University of Science and Technology (HKUST), will give the keynote speech \u201cQuality Big Data\u201d and the research team members of the Quality and Data Analytics Laboratory will make presentations of their research topics.<\/p>\n
Prof. Tsung is a Chair Professor of the Department of Industrial Engineering and Decision Analytics (IEDA) at HKUST, where he leads the Quality and Data Analytics Lab. Prof. Tsung has a proven record of academic leadership and has also a strong research record in the area of Quality and Data Analytics.<\/p>\n
We hope many young researchers and students will join this symposium and obtain fresh inspiration for advanced data analytics from the speeches and discussions towards future researches.<\/p>\n
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14:00 Opening remarks<\/strong> 14:05 Keynote lecture<\/strong> 15:15 Short speech<\/strong> 15:45 Student collaboration session<\/strong> 17:15 Closing remarks<\/strong> <\/p>\n
\n– Director Toshiyasu Matsushima (Center for Data Science, Waseda Univ.)<\/p>\n
\nQuality Big Data
\n– Prof. Fugee Tsung (Hong Kong Univ. of Science & Technology)<\/p>\n
\nStructured Functional Principal Component Analysis for Multivariate Profile Data
\n– Dr. Kai Wang (Hong Kong Univ. of Science & Technology)<\/p>\n
\nA Statistical Transfer Learning Approach to Improve Passenger Inflow Forecasts
\n– Mr. Zhenli Song (Hong Kong Univ. of Science & Technology)
\nTensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction
\n– Mr. Ziyue LI (Hong Kong Univ. of Science & Technology)
\nCustomer Satisfaction Monitoring through Integrating Online and Offline Data
\n– Ms. Yinghui Huang (Hong Kong Univ. of Science & Technology)
\nAn analytical model of employees’ communication data on a chat system based on topic models
\n– Ms. Ayako Yamagiwa (Waseda Univ.)
\nA Bayesian Decision-Theoretic Change-Point Detection for i.p.i.d. Sources
\n– Mr. Kairi SUZUKI (Waseda Univ.)<\/p>\n
\n– Prof. Manabu Kobayashi (Center for Data Science, Waseda Univ.)<\/p>\nRegistration<\/h4>\n