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學(xué)術(shù)動(dòng)態(tài)

學(xué)術(shù)動(dòng)態(tài)

學(xué)術(shù)活動(dòng)

信息管理系大數(shù)據(jù)與管理高端講座【2】

作者: 編輯: 發(fā)布時(shí)間:2017-06-16

題目:An Industrial Engineering Perspective of Data Science


報(bào)告人:黃帥教授


時(shí)間:6月22日上午9:00-11:30


地點(diǎn):bwin必贏唯一官網(wǎng)大樓121


報(bào)告摘要:


Data Science is not new to Industrial Engineers. As earlier as in the 90s of the 20th century, the term Data Science has been coined in numerous research publications in Industrial Engineering areas such as statistical quality control, engineering statistics, and design of experiments. This tradition of integrating statistics with operations research for system engineering has been the backbone of conducting systematic operations in many industries, nurturing generations of workforces in different areas and continuing to inspire novel researches as an evergreen academic area. In this workshop, Dr. Shuai Huang will share his experience with graduate and undergraduate students and faculty members at XJTU who are interested on data-driven research in Industrial Engineering to solve real-world problems with innovations in both statistics and operations research.


黃帥教授個(gè)人簡(jiǎn)介:

Dr. Shuai Huang is an Assistant Professor at the Department of Industrial and Systems Engineering at the University of Washington. He received a B.S. degree on Statistics from the University of Science and Technology of China in 2007 and a Ph.D. degree on Industrial Engineering from the Arizona State University in 2012. He is also an adjunct faculty member at the Department of Biomedical Informatics and Medical Education (BIME) and the Integrated Brain Imaging Center (IBIC) at the University of Washington. Dr. Huang develops methodologies for modeling, monitoring, diagnosis, and prognosis of complex networked systems such as the brain connectivity networks, manufacturing systems, and disease progression process of complex diseases that have multiple stages and pathways. He also develops statistical and data mining models to integrate massive and heterogeneous datasets such as neuroimaging, genomics, proteomics, laboratory tests, demographics, and clinical variables, for facilitating scientific discoveries in biomedical research and better decision-makings in clinical practices. His research is funded by the National Science Foundation, National Institute of Health, Juvenile Diabetes Research Foundation, Helmsley Foundation, and several biomedical research institutes. Dr. Huang currently serves as Associate Editor for the IIE Transactions in Healthcare Systems Engineering and Quality Technology and Quantitative Management.


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