GAMES Webinar 2021 – 169期(可视化专题) | Ross Maciejewski (Arizona State University)
【GAMES Webinar 2021-169期】(可视化专题)
报告嘉宾：Ross Maciejewski (Arizona State University)
报告时间：2021年1月7日晚上8:00（北京时间）
报告题目：Visualization, Artificial Intelligence, and Decision Making
报告摘要：
In the era of Big Data, Artificial Intelligence and Machine Learning have made immense strides in developing models for real-world phenomena. To date, applications of these models are being deployed to make decisions about healthcare, bank loans, and numerous other critical tasks. However, as artificial intelligence solutions have become more wide-spread, there has been a growing need for humans to be able to understand how and why these models have made a decision. In this talk, I will discuss the roles that visualization plays in supporting artificial intelligence and decision making from model building to decision support systems. Along the way, I will discuss how visualization has focused on opening the black-box of machine learning models, provide examples of visual analytics tools for decision support, and discuss emerging challenges and opportunities in Human-AI Teaming for Decision-Making.
讲者简介：
Ross Maciejewski is an Associate Professor at Arizona State University in the School of Computing, Informatics & Decision Systems Engineering and Director of the Center for Accelerating Operational Efficiency (CAOE) – a Department of Homeland Security Center of Excellence. His primary research interests are in the areas of visual analytics, explainable AI and decision making. Professor Maciejewski is a recipient of an NSF CAREER Award (2014) and was named a Fulton Faculty Exemplar (2017) and Global Security Fellow at Arizona State. His work has been recognized through a variety of awards at the IEEE Visual Analytics Contest (2010, 2013, 2015), a best paper award in EuroVis 2017, and a CHI Honorable Mention Award in 2018.
讲者个人主页: http://rmaciejewski.faculty.asu.edu
主持人简介：
马昱欣，亚利桑那州立大学计算机系VADER实验室博士后，将于2021年夏加入南方科技大学计算机系任助理教授。其先后于2012年、2017年在浙江大学获得学士及博士学位，2016年在新加坡国立大学SeSaMe研究中心做实习研究员，主要研究方向为可视分析、信息可视化和可解释人工智能。目前已发表论文20余篇，其中多篇长文发表于IEEE VIS、TVCG、CG&A等国际重要会议期刊。曾参与可视化专著及教材编写2部。个人主页：https://mayuxin.me
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