Abstract: 

Visualisation is getting increasing interest as an integral part of the data science profession. Most of this interest is currently focused on incorporating visualisation only as a communication medium towards the end of an analysis process. However, visualisation has much more to offer — with computational models becoming increasingly complex to generate and interpret, visualisation opens up exciting possibilities in how data science is practised. Recent advances in visualisation research, in particular in visual analytics, devise new roles for interactive visualisation as a facilitator of human and machine cooperation in solving complex, ill-defined problems. In this talk, we will walk through both the conventional and advanced visualisation approaches to set the scope for incorporating visualisation in data science processes. The talk will then visit recent advances in visualisation research, and discuss opportunities, and touch upon future trends.

Bio: 

Cagatay is a Senior Lecturer in Applied Data Science at the Department of Computer Science at City, University of London and a member of giCentre — a world-leading research centre in visualisation research. He is also the director for the MSci in Data Science programme at City. He has a PhD in Visualisation from University of Bergen, Norway, with a background in computer science. His research mainly focuses on designing visualisations, interactions and computational methods to enable effective combinations of human and machine capabilities to facilitate data-intensive problem solving. He works together with experts in various domains such as biomedicine, transport, intelligence, cyber security and social science, to name a few. He actively contributes in various roles to journals and conferences within visualisation and computer graphics and, leads and contributes to a number of national, international, and industry-funded research projects.