User-centric Visual Analytics towards Data Exploration and Analysis
Visual Analytics brings the visual perception and intelligence means to the data exploration and analysis process. However, the question arises how to make the resulting visual analytics systems more user-centric with the aim of enabling domain experts to perform data exploration and analytical tasks more effectively and efficiently. In this talk, I will focus on this problem from three perspectives: 1) designing intuitive and novel visualizations to help domain experts understanding their data in a better and meaningful way, 2) building interactive visual analytics tools and systems to help domain experts making use of advanced visual data analytics techniques so they can come up with well-informed decisions, and 3) evaluating the designed visualizations and the developed visual analytics tools and systems to make sure that they fulfil the demands of the underlying domain and the users. A number of case studies from my previous and current work will be shown from the domains of data science, software systems, and social media to show the applicability and efficacy of user-centric visual analytics towards data exploration and analysis.
Shah Rukh Humayoun is currently working as a Postdoctoral Research Scholar in the Visual Analytics Lab (VALT) at Tufts University. He received his Bachelor degree in Computer Science from the University of the Punjab, MSc in Software Engineering from the University of York, and PhD in Computer Engineering from the Sapienza University of Rome. Previously, he has worked as Postdoctoral Research Scholar in the Computer Graphics and HCI Lab at the University of Kaiserslautern and Research Assistant in the Department of Computer Science at the Sapienza University of Rome. He has the academic experience of studying and working in five countries across three continents. His current research interests include visual analytics, information visualization, and human-computer interaction. He is currently involved in DARPA funded “Data-Driven Discovery of Models (D3M)” project, which aims at developing automated model discovery systems to enable subject matter experts to construct and manage empirical models of complex systems without having experience or knowledge of machine learning or data science. He has been in the PC and in organizational roles in many high ranked conferences such as CSCW, IUI, ISS, AVI, and MOBILESoft. He was the General Chair of UsARE 2014 and 2017 workshops conducted in conjunction with RE 2014 and 2017. He enjoys doing reviewing regularly in the leading conferences of his research areas.