Keerthana Jegatheesan
Chalmers University of Technology
Digital Research Engineer
Role In Infravis
Application Expert
Experienced In
Data analysis/wrangling/scraping, 2D visualization of large datasets, dimensionality reduction using unsupervised ML, complex astrophysics data (photometry and 3D spectroscopy).
Tools Used Frequently
Python visualization libraries (matplotlib, seaborn, bokeh, plotly), SQL, astronomy-specific tools (astropy, DS9, QFitsView, etc.).
About
I am a Digital Research Engineer at Chalmers, working at the intersection of data analysis and visualization. With a background in Astrophysics, I have been involved in projects with large volumes of structured and unstructured data. My PhD thesis was centred on analysing nearby galaxies using Integral Field Spectroscopy (in the form of datacubes), by modelling them and building 2D maps and plots to visualize and estimate physical parameters, as well as interactive tools to pre-process datacubes. I have also worked on a data-driven method to estimate physical parameters using unsupervised Self-Organizing Maps on galaxy survey data.
At InfraVis, I hope to bring this background to support researchers in diverse visualization projects.