GAMES Webinar 2021 – 171期(可视化专题) | Remco Chang (Tufts University)

【GAMES Webinar 2021-171期】(可视化专题)

报告嘉宾:Remco Chang (Tufts University)


报告题目:Data Systems for Human Data Interaction


Visualization and visual analytics have become an integral part of data science. With the democratization of data and data analysis, visualization is now used by scientists, domain experts, decision makers, and everyday citizens. Such widespread use of visualization has subsequently increased the challenge of designing generalizable and scalable systems that can suit the diverse needs of a wide audience. In this talk, I will present research projects at the Visual Analytics Lab at Tufts (VALT) that aim to address the challenge. The two types of data systems we have developed are: (1) AI and machine learning based visual analytics systems for human-guided data analysis, and (2) database systems that enable the interactive exploration of gigabytes of data with minimal latency. Although the techniques used in these systems span disciplines, the glue that ties these systems together is in their facilitation of human-in-the-loop data analysis.


Remco Chang is an Associate Professor in the Computer Science Department at Tufts University. He received his BA from Johns Hopkins University in 1997 in Computer Science and Economics, MSc from Brown University in 2000, and PhD in Computer Science from UNC Charlotte in 2009. Prior to his PhD, he worked for Boeing developing real-time flight tracking and visualization software, followed by a position at UNC Charlotte as a research scientist. His current research interests include visual analytics, information visualization, HCI, and databases. His research has been funded by the NSF, DARPA, the Walmart Foundation, Army, Navy, DHS, MIT Lincoln Lab, and Draper. He has had best paper, best poster, and honorable mention awards at InfoVis, VAST, CHI, and VDA. He was the papers chair for the IEEE Visual Analytics conference (2018-2019) and is currently an associate editor for the ACM TiiS journal. He received the NSF CAREER Award in 2015.


陈思明,复旦大学大数据学院青年研究员。曾任德国弗劳恩霍夫智能分析和信息系统研究所(Fraunhofer IAIS)研究员与德国波恩大学的博士后研究员。于2011年获复旦大学理学学士学位,2017年获北京大学计算机科学专业理学博士学位。从事大数据可视化与可视分析的研究,主要研究方向包括:社交媒体数据可视分析、城市时空数据可视分析,网络安全与用户行为可视分析及故事叙述,共发表论文40余篇,其中在IEEE VIS,IEEE TVCG,EuroVis等顶级国际可视化会议以及期刊上发表10余篇文章。担任多个国际会议的组织委员会和程序委员会成员,包括IEEE PacificVis海报主席、宣传主席,ChinaVis数据分析挑战赛主席,IEEE VIS程序委员会委员等。他的工作曾获得6次IEEE VAST Challenge数据挑战赛一等奖,以及多个会议最佳论文/海报(提名)奖,包括IEEE VAST最佳海报提名奖,EuroVA最佳论文奖、Agile最佳海报奖、ChinaVis最佳论文提名奖等。更多信息请登录: 查看。

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