Bio: Dr Mai Elshehaly is an Assistant Professor in Computer Science at the University of Bradford. She holds a PhD and MSc. in Computer Science from the Center for Human-Computer Interaction at Virginia Tech. Before her current appointment, she held post-doctoral fellowships at the University of Leeds and University of Maryland, Baltimore County. Her primary research interests are in Human-Computer Interaction and Visual Analytics, particularly the human-centred design of visualisation and AI that support collaborative decision-making. She is especially interested in the role of data visualisation in improving communication between decision makers and underrepresented communities. Mai is a member of the advisory board for the Wolfson Centre for Applied Health Research, she leads the Digital Education theme within the Centre for Applied Education Research (CAER), and is the University of Bradford lead for the Digital Divide theme within the Child of the North initiative (a large project organised by nine research intensive universities in the North of England, aimed at improving outcomes for children). Mai is also co-Director of the Digital Makers Programme, a cross-sector initiative that is building a data science approach to the digital upskilling of children and young people.
Abstract: Information visualisation presents several opportunities for decision-makers and communities to make better-informed decisions, driven by data insights. However, many of these opportunities are missed due to a communication gap between visualisation designers and tool developers on one end, decision-makers on another, and communities whose data are represented in the visualisation on a third. This gap is exacerbated by varying levels of digital literacy and engagement with technology. In this talk, we will discuss some of the opportunities for visual analytics research to bridge this communication gap and we will highlight key challenges that hinder the usability of available data, such as Connected Bradford, to inform population health management decisions.
