时间：2016年11月11日 10：00-11：00 地点：华东师范大学中山北路校区数学馆201报告厅 主办单位：华东师范大学数据科学与工程学院摘要 Since sequencing of the human genome in 2003, we have dreamed about managing patient health more effectively based on their genomic profiles. Such a dream remains elusive. “The fundamental difficulty lies in the complexity of biological systems that have evolved through billions of years.” On the other hand, major progress can be and has been made in "personalized medicine" by applying AI machine learning on massive patient medical data accumulated. In essence, we can uncover new insight from the data to improve patient health without knowing the biology behind it. Such new insight is then added back into the medical knowledge to form a richer knowledge graph for personalized medicine, predictive patient modeling, patient risk assessment, public health monitoring, etc. Exploiting patient medical data brings another set of management problems, namely the heterogeneous nature of data sources and taxonomies, the enormous size of data volume, and huge analytic processing requirements. At this talk, we will discuss all these issues and show some case studies at a major research hospital in New York City.报告人简介 Dr. Sheng-Chuan Wu is a Vice President at the leading Artificial Intelligence and Semantic Technology company, Franz Inc, in Silicon Valley. While at Franz, Dr. Wu has collaborated with Bioinformatics experts from Harvard Medical School, Stanford University and Astra Zeneca, working with massive biological data. He has been focusing on Semantic Technology over the last 10 years, and routinely lectured and keynoted on Artificial Intelligence and Semantic Technology at conferences. Most recently, he keynoted at PRICAI2016, CCKS2016, KMO2016 and KSEM2015 on Healthcare Analytics. He has, since 2007, conducted more than 20 weeklong workshops on Semantic Technology and Artificial Intelligence in Asian countries. Dr. Wu has also consulted on several Big Data and Semantic Technology projects in the US and Asia. 华东师范大学数据科学与工程学院