I am a Marie Curie Postdoctoral scholar with Sheelagh Carpendale in her InnoVis group at the Interactions Lab at Department of Computer Science, University of Calgary. My research focuses on information visualization and human-computer interaction.
I am interested in supporting people in understanding and making sense of data. My dissertation research concerned understanding the benefits of using large, high-resolution displays to support this goal through interaction techniques and data visualization.
- Dagstuhl seminar
- 2018 Gairdner International Symposium
- Quick visit at Aarhus University
- Attending VIS 2018 in Berlin
- Grant reviewer for Marie Curie September 2018 call
- Talk at Tamara Munzner’s group at UBC in Vancouver, BC
- Talk at Tableau Research in Palo Alto, California
- Talk at Microsoft Research, Redmond, Washington
- Talk in Jessica Hullman and Jeff Heer’s group at University of Washington in Seattle
- ACM CHI 2018 In Montreal was super exciting!
- WHO meeting in Banff, Alberta
- VIS 2017 in Phoenix, Arizona and ISS 2017 in Brighton, UK
- I will be at CHI 2017 in Denver, Colorado
- My Marie Curie proposal is accepted!
2020 | Postdoctoral scholar
2018-2019 | Marie Curie Postdoctoral scholar
2017 | Postdoctoral scholar
2016 | Postdoctoral scholar
With Mikkel Jakobsen, part of BIOPRO research project. Human Centered Computing at University of Copenhagen, Denmark
2015 | Postdoctoral scholar
With teaching obligations at the Communication and IT study programme. Human Centered Computing at University of Copenhagen, Denmark
2011-2015 | Ph.D. student
Supervised by Kasper Hornbæk WallViz research project. Human Centered Computing at University of Copenhagen, Denmark
2009-2010 | Research Proposal Writer
targeting the 7th EU framework programme for research and development. Danish Innovation Institute — part of the Pera Innovation Network, Kgs. Lyngby, Denmark
Complex data visualization design projects often entail collaboration between people with different visualization-related skills. For example, many teams include both designers who create new visualization designs and developers who implement the resulting visualization software.
PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System
We present a visual analytics tool for collaboratively exploring data from patient administrative systems on large touch displays in meeting contexts. Large touch displays are becoming commercially available, but we have limited knowledge about how they might be used in such a context. We investigated this with our system, PatientAdministrativeDataExplorer (PADE).
We present a visualization that makes use of a novel highlighting and animation technique. The primary motivation behind the design of this visualization was to enable people to look at data about healthcare services, and specifically to increase their knowledge about the impact of the amount of healthcare workers per capita.
We present our preliminary results of an international survey on the practical adoption and use of the International Classification of Diseases (ICD) from a visualization and visual analytics perspective. The ICD system, in different versions, is globally used for coding morbidity and mortality statistics, however, coding practices vary across countries.
We present Biomole, an interactive visualization designed to explore a data set created to support bio-inspiration design published by the Ask Nature organization. The Ask Nature data set contains a hierarchy of functions which we encode within different visual elements of Biomole; most importantly interactive data painting of functions allows people to search for functional co-occurrence.
In creating visualization for the general public, we have concerns relating to visual representations and data provenance, trust, and truth. We briefly outline the context of our work, describe our concerns and their relation to philosophy.
In this position paper, we discuss our prior and current work on data science work practices and how these might be supported by ubiquitous analytics tools. We argue collaborative tools might reduce risks of false conclusions based on ill-conceived understandings of data sets.
Visualization systems with multiple views are often used to represent data from different perspectives. There are many advantages in doing so, such as providing a way for users to understand a dataset by revealing its various attributes in separate views and offering additional information that could be more useful than if it was just one graph.