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学术讲座:30 years of data analytics: what have we learnt?

时间:2019-06-28 16:17:51 文章来源 :学科 浏览量:<span id="hitcount2189471">112</span><script src="http://search.hznu.edu.cn/zcms/counter?Type=Article&ID=2189471&DomID=hitcount2189471"></script>

报告题目:30 years of data analytics: what have we learnt?

主讲人:刘小惠 博士

时间:2019年7月2日 (周二)下午15:00-16:30

地点:勤园12-304

主讲人简介:

刘小惠博士,2000任英国布鲁奈尔大学计算机科学终身教授,多年来刘教授从事人工智能和数据科学研究及在其他领域的应用,共发表学术论文(SCI)300余篇,自2014起连续是高被引研究员。1995年创建了国际智能数据分析会议,2005年获IDA奠基人奖,多次担任英国皇家统计学会和几个国家研究基金会顾问,曾任荷兰莱顿(Leiden)大学帕斯卡尔(Pascal)名誉教授,哈佛医学院访问科学家和中国科学院访问教授。

内容摘要:

Over the past 30 years, we have witnessed an exponential growth of data as well as our continuing drive in making good sense of them. However, the widening gap between data generation and data comprehension, a phenomenon observed almost three decades ago, is still there and probably getting worse. In this talk, I will take a personal journey to look at key developments in this challenging interdisciplinary field, and examine what has worked and also on what has not yet. Issues deserving much more attention than they currently receive will be highlighted, and examples will be drawn from diverse fields including biology, computing, engineering and health.

欢迎各位师生参加!


学术动态

学术讲座:30 years of data analytics: what have we learnt?

学科 · 2019-06-28

报告题目:30 years of data analytics: what have we learnt?

主讲人:刘小惠 博士

时间:2019年7月2日 (周二)下午15:00-16:30

地点:勤园12-304

主讲人简介:

刘小惠博士,2000任英国布鲁奈尔大学计算机科学终身教授,多年来刘教授从事人工智能和数据科学研究及在其他领域的应用,共发表学术论文(SCI)300余篇,自2014起连续是高被引研究员。1995年创建了国际智能数据分析会议,2005年获IDA奠基人奖,多次担任英国皇家统计学会和几个国家研究基金会顾问,曾任荷兰莱顿(Leiden)大学帕斯卡尔(Pascal)名誉教授,哈佛医学院访问科学家和中国科学院访问教授。

内容摘要:

Over the past 30 years, we have witnessed an exponential growth of data as well as our continuing drive in making good sense of them. However, the widening gap between data generation and data comprehension, a phenomenon observed almost three decades ago, is still there and probably getting worse. In this talk, I will take a personal journey to look at key developments in this challenging interdisciplinary field, and examine what has worked and also on what has not yet. Issues deserving much more attention than they currently receive will be highlighted, and examples will be drawn from diverse fields including biology, computing, engineering and health.

欢迎各位师生参加!