Associate Professor, University of Utah
We present TopoLines, a method for smoothing line charts using techniques from Topological Data Analysis. The design goal of TopoLines is to maintain prominent peaks in the data while minimizing any residual error. We evaluate TopoLines for 2 visual analytics tasks by comparing to 5 popular line smoothing methods with data from 4 application domains.
Continue readingIn this paper, we discuss the construction and application of peer review in a computer science visualization course, including: projects that reuse code and visualizations in a feedback-guided, continual improvement process and a peer review rubric to reinforce key course concepts.
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In this paper, we leverage persistent homology features of an undirected graph as derived information for interactive manipulation of force-directed layouts. We first discuss how to efficiently extract 0-dimensional persistent homology features from both weighted and unweighted undirected graphs. We then introduce the interactive persistence barcode used to manipulate the force-directed graph layout by adding and removing contracting and repulsing forces generated by the persistent homology features, eventually selecting the set of persistent homology features that most improve the layout.
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A key problem in Deep Brain Stimulation (DBS) is determining the optimal parameters for clinical outcome. Current knowledge does not provide a complete deterministic model of DBS neurophysiology. While multiple parameters may influence clinical outcomes in DBS, this paper explores spatial correlation of volume of tissue activated (VTA) to Unified Parkinson’s Disease Rating Scale (UPDRS) scores.
Continue readingIn this position paper, we define three methods — re-evaluation, expansion, and specialization — for embedding a replication study into a novel published work. Within this context, we provide a non-exhaustive case study on replications of Cleveland and McGill’s seminal work on graphical perception.
Continue readingPairing critical points enables forming topological fingerprints, known as persistence diagrams, that provides insights into the structure and noise in data. In this paper, we discuss two algorithmic approaches for pairing critical points in Reeb graphs, first a multipass approach, followed by a new single-pass algorithm, called Propagate and Pair.
Continue readingIn this paper, we leverage the contour tree to extract a hierarchical representation of the topology of an image. We propose 4 topology-aware transfer functions for editing features of the image using local topological properties, instead of global image properties.
Continue readingThis project addresses two important scientific questions: how to effectively use topology to extract features from ensembles; and how to design visualizations for domain experts that efficiently communicate the features. To extract features from an ensemble, the project will investigate new methods of robustly comparing and contrasting the topology of multiple ensemble realizations. Then, it will design new visualization methods for efficiently and effectively comparing and exploring the features and variations within ensembles.
Continue readingThis research paper employs a data-driven, explainable, and scalable approach to the development and application of an online peer review form in computer science and engineering courses.
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This paper introduces and extension to our previous papers to handle anomalies in the point based object slicing method. The anomalies handled are point, line and plane touch cases as well as overlaps.
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