Dr Sara Fernstad
- Email: email@example.com
I am a Lecturer in Data Science with ten years' experience of Information Visualization research. Before joining the School of Computing Science at Newcastle University, I was a Senior Lecturer in Computer Science at University of Northumbria at Newcastle. Prior to that I held post-doctoral research positions at Cambridge University, UK, and at Unilever R&D, UK. I completed my PhD on algorithmically guided visualization for analysis of high dimensional and heterogeneous data in 2011, at Linköping University in Sweden.
My main research interests are in the area of Information Visualization and particularly in challenges relating to incomplete (missing), high dimensional and heterogeneous data, visualization of biomedical and ‘omics-type’ data, and the combination of visualization and data mining methods.
My main research interests are in the field of Information Visualization (Visual Analytics/Data Visualization) and I am particularly interested in challenges relating to high dimensional data, heterogeneous data and uncertainty in data. These challenges are all highly relevant in a range of application domains, not least in biomedical domains and life sciences, which are becoming more and more data driven.
From a methodological point of view, my interests are focused around the combination of visualization and data mining methods and user-centred design approaches. Visualization and data mining both address the same type of challenges, with similar goals but with slightly different approaches and strengths. By combining the two we may be able to find better solutions to major data analysis challenges.
My research to date can broadly be separated into four major themes, which ever so often crosses each other’s paths: Visualization of Missing Data, Visual Exploration of Microbial Populations, Interactive Visual Exploration of High Dimensional Data, and Visualization of Heterogeneous Data. As an overarching theme to this lies the concept of 'interestingness'. How do we bring out the most interesting and useful information in a dataset? How do we define what is interesting? How can we use 'interestingness' to support knowledge discovery and gaining of insights in the most useful way?
Google scholar profile: https://scholar.google.com/citations?user=DKcE7HwAAAAJ&hl=en&oi=ao
- Grube M, Gaya E, Kauserud H, Smith AM, Avery SV, Fernstad SJ, Muggia L, Martin MD, Eivindsen T, Kõljalg U, Bendiksby M. The next generation fungal diversity researcher. Fungal Biology Reviews 2017, 31(3), 124-130.
- Stewart CJ, Skeath T, Nelson A, Fernstad SJ, Marrs ECL, Perry JD, Cummings SP, Berrington JE, Embleton ND. Preterm gut microbiota and metabolome following discharge from intensive care. Scientific Reports 2015, 5, 17141.
- Stevens D, Cornmell R, Taylor D, Grimshaw SG, Riazanskaia S, Arnold DS, Fernstad SJ, Smith AM, Heaney LM, Reynolds JC, Thomas CLP, Harker M. Spatial variations in the microbial community structure and diversity of the human foot is associated with the production of odorous volatiles. FEMS Microbiology Ecology 2015, 91(1), 1-11.
- Fernstad SJ, Glen RC. Visual analysis of missing data - To see what isn't there. In: IEEE Visual Analytics Science and Technology. 2014, Paris, France: IEEE.
- Fernstad SJ, Shaw J, Johansson J. Quality-based guidance for exploratory dimensionality reduction. Information Visualization 2013, 12(1), 44-64.
- Fernstad SJ, Johansson J, Adams S, Shaw J, Taylor D. Visual exploration of microbial populations. In: Biological Data Visualization (BioVis), 2011 IEEE Symposium on. 2011, Providence, RI, USA: IEEE.
- Fernstad SJ, Johansson J. A task based performance evaluation of visualization approaches for categorical data analysis. In: Information Visualisation (IV), 2011 15th International Conference on. 2011, London, UK: IEEE.
- Johansson S, Johansson J. Visual analysis of mixed data sets using interactive quantification. ACM SIGKDD Explorations Newsletter 2010, 11(2), 29-38.
- Johansson S, Johansson J. Interactive dimensionality reduction through user-defined combinations of quality metrics. IEEE Transactions on Visualization and Computer Graphics 2009, 15(6), 993-1000.
- Johansson S. Visual exploration of categorical and mixed data sets. In: ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration. 2009, Paris, France: ACM.
- Johansson S, Knaving K, Lane A, Jern M, Johansson J. Interactive exploration of ingredient mixtures using multiple coordinated views. In: Information Visualisation, 2009 13th International Conference. 2009, Barcelona, Spain: IEEE.
- Johansson S, Jern M, Johansson J. Interactive quantification of categorical variables in mixed data sets. In: Information Visualisation, 2008. IV '08. 12th International Conference. 2008, London, UK: IEEE.