My primary research includes the characterization, design, and evaluation of visual-interactive interfaces to combine the strengths of both humans and algorithms in interactive machine learning and data science applications. My data-centered focus is on time series data as well as multivariate data. My technique-driven focus ranges from unsupervised to supervised machine learning including cluster analysis, dimensionality reduction, active learning, regression analysis, and classification. From a task perspective most of my work supports exploratory data analysis, i.e., sense-making, decision-making, and hypotheses-building for undiscovered data. Important application domains so far include climate and Earth observation, digital libraries, human motion analysis, service and energy network analysis, political decision-making, music classification, sports data analysis, stock chart analysis, as well as medical and patient-related research in particular.
Jürgen Bernard is an Assistant Professor of Computer Science at the University of Zurich (UZH), Switzerland. He is leading the Interactive Visual Data Analysis (IVDA) Group.
Jürgen Bernard studied Computer Sciences with focus on Computer Graphics and Bio Technology at the University of Technology of Darmstadt. His Diploma thesis in 2009 was about the visual-interactive cluster analysis using neural networks. He received his PhD Degree in 2015, when he was with Fraunhofer IGD. His thesis was about “Exploratory Search in Time-Oriented Primary Data”. In 2016, Jürgen Bernard started as a Post-doc researcher at TU Darmstadt at Interactive Graphics Systems Group, leading the Visual-Interactive Machine Learning Group. In 2019, Jürgen Bernard became a postdoctoral research fellow at the University of British Columba, Vancouver, Canada, where he joined the InfoVis group, led by Professor Tamara Munzner.