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太原理工大学

关于Queen's University教授Patrick Martin来我校作学术报告的通知

发布时间:2017-05-16 来源:计算机学院 作者:牛保宁

报告内容:Consumable analytics attempt to address the shortage of skilled data analysts in many organizations by offering analytic functionality in a form more familiar to employees. Providing consumable analytics for big data faces three main challenges: the large volumes of data require efficient distributed algorithms; the analytics must offer an easy interface to allow in-house experts to use these algorithms while minimizing the learning cycle and existing code rewrites, and the analytics must work on data of different formats stored on heterogeneous data stores. The talk will explore the above challenges and will give an overview of our efforts to provide consumable analytics for big data.

报告内容:Consumable analytics attempt to address the shortage of skilled data analysts in many organizations by offering analytic functionality in a form more familiar to employees. Providing consumable analytics for big data faces three main challenges: the large volumes of data require efficient distributed algorithms; the analytics must offer an easy interface to allow in-house experts to use these algorithms while minimizing the learning cycle and existing code rewrites, and the analytics must work on data of different formats stored on heterogeneous data stores. The talk will explore the above challenges and will give an overview of our efforts to provide consumable analytics for big data.

标题:Consumable Analytics for Big Data

报告人:Patrick Martin博士,Queen’s University教授

时间:2017年5月19日10:00 – 11:00

地点:明向校区计算机科学与技术学院一层报告厅

Patrick Martin于1984年获多伦多大学计算机科学博士学位;1984年至今在Queen's University计算机学院历任助理教授、副教授和教授,2002至2007年任计算机学院副院长,2004-2005任计算机学院执行院长;1994年至今任IBM多伦多实验室访问科学家,1991年任日内瓦大学特邀教授;主持包括加拿大自然科学与工程基金重点项目、安大略研究基金重大项目、IBM CAS等项目在内的项目20多项;在TKDE、ACM Computer Survey、IEEE Transaction on Cloud Computing、IBM Systems Journal等期刊和著名国际会议发表论文240多篇;是加拿大自然科学与工程基金、安大略研究基金、CITO等的评审委员会委员;1999年获Howard Stavely Award。研究兴趣包括Database system performance、Autonomic systems、Data-intensive cloud services、Analytics-as-a-Service等。

此次学术报告会由计算机学院组织,欢迎广大师生踊跃参加。

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