Hello folks,

This is a reminder that we are having Chris Collins' talk and student round table today:

Talk: *Galbraith (GB303), 11:00am* Round Table: *Bahen (BA5187 -- access via BA5166), 4:00pm*

Hope to see you there, Nicole

-------------- *Abstract: *The classic information visualization design pattern of “overview first, zoom and filter, details on demand” is no longer sufficient. As datasets have grown (and small displays have become more prevalent), simple overviews tend to be either too high-level to be useful, or too cluttered to reveal anything interesting. The task of exploring and sifting through the data is left only to the analyst in this traditional model. It doesn't have to be this way: well-designed computational models of various sorts can augment the analysis process by highlighting patterns and drawing attention to regions of potential interest. I seek to facilitate a closely coupled interaction between people and underlying computational models, mediated by visualizations which include algorithmic transparency as to what guidance is being provided or what data is being hidden. In this talk I will discuss several recent research projects which use various types of models to improve the human-computer visual analytic complex. Linguistic, interaction, information, and perception models can provide data- driven visualization views and create suggestions of starting points for analysis, just-in-time data curation, and guidance for next steps. I will discuss my vision for the future of mixed-initiative analytics which builds on transparent and understandable algorithms, including explainable machine learning, combined with highly interactive and powerful visualizations.

*Bio:* Christopher Collins is the Canada Research Chair in Linguistic Information Visualization and an Associate Professor of Computer Science at the University of Ontario Institute of Technology (UOIT). His research focus is interdisciplinary, combining information visualization and human-computer interaction with natural language processing, with a focus on interaction design and guidance in visual analytics. While his group is best known for text visualization, he collaborates across a wide variety of topics, including health informatics, machine learning, and computer security. His papers have been published in many venues including IEEE Transactions on Visualization and Computer Graphics, have received awards at IEEE VIS, and have been featured in popular media such as the CBS News and the New York Times Magazine. Dr. Collins is a past member of the executive of the IEEE Visualization and Graphics Technical Committee and regularly serves on the IEEE VIS Conference Organizing Committee. He received his PhD in Computer Science from the University of Toronto.

2018-02-22 15:36 GMT-05:00 Nicole Sultanum nicolebs@dgp.toronto.edu:

Hello folks,

We will have another candidate for the data vis position, *Chris Collins*, visiting on *Monday Feb 26*. Events of interest include:

• His talk is at *11am, at GB303*
• The student round table will be at *4PM @ BA 5187*

Abstract of the talk and bio follow below, for your convenience.

Also, please note that the candidate has asked to keep his application *confidential*. As such, please* do not circulate this note or advertise this event* to anyone outside UofT. Thanks!

Hope to see you all on Monday,

Nicole

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*Title*: Mixed-Initiative Visual Analytics: Model-driven Views and Analytic Guidance

*Presented By*: Christopher Collins, University of Ontario Institute of Technology

*Abstract*: The classic information visualization design pattern of “overview first, zoom and filter, details on demand” is no longer sufficient. As datasets have grown (and small displays have become more prevalent), simple overviews tend to be either too high-level to be useful, or too cluttered to reveal anything interesting. The task of exploring and sifting through the data is left only to the analyst in this traditional model. It doesn't have to be this way: well-designed computational models of various sorts can augment the analysis process by highlighting patterns and drawing attention to regions of potential interest. I seek to facilitate a closely coupled interaction between people and underlying computational models, mediated by visualizations which include algorithmic transparency as to what guidance is being provided or what data is being hidden. In this talk I will discuss several recent research projects which use various types of models to improve the human-computer visual analytic complex. Linguistic, interaction, information, and perception models can provide data-driven visualization views and create suggestions of starting points for analysis, just-in-time data curation, and guidance for next steps. I will discuss my vision for the future of mixed-initiative analytics which builds on transparent and understandable algorithms, including explainable machine learning, combined with highly interactive and powerful visualizations.

*Biography*: Christopher Collins is the Canada Research Chair in Linguistic Information Visualization and an Associate Professor of Computer Science at the University of Ontario Institute of Technology (UOIT). His research focus is interdisciplinary, combining information visualization and human-computer interaction with natural language processing, with a focus on interaction design and guidance in visual analytics. While his group is best known for text visualization, he collaborates across a wide variety of topics, including health informatics, machine learning, and computer security. His papers have been published in many venues including IEEE Transactions on Visualization and Computer Graphics, have received awards at IEEE VIS, and have been featured in popular media such as the CBS News and the New York Times Magazine. Dr. Collins is a past member of the executive of the IEEE Visualization and Graphics Technical Committee and regularly serves on the IEEE VIS Conference Organizing Committee. He received his PhD in Computer Science from the University of Toronto.