I am WEAVE-LOFAR postdoctoral researcher at Nottingham University. My interests lie in mainly in applying Bayesian analysis to big data. Therefore, during my Ph.D. I got involved with the latest data from LOFAR, Herschel-ATLAS, and SDSS.
My research attempts to quantify and then disentangle scatter and selection effects from well-known scaling relations. My most recent work includes charaterising how the the relationship between the far-infrared and low frequency radio emission (FIRC) from star-forming galaxies changes over the properties of those galaxies (paper).
I have also branched out to develop photometric reverberation mapping techniques for use with large photometric surveys such as LSST.
Currently, I’m developing a Gaussian mixutre model technique CANDID that can mitigate the effects of astronomical biases and incomplete datasets whilst also modelling an entire multidimensional distribution. I am applying this technique to explore the causes of the mass dependency of the star-formation rate – radio luminosity relation (see Gulay’s paper). To do this, I am using the latest LOFAR data release (DR2) together with Horizon-AGN simulation to model the full distribution of star-forming properties over redshift and associate it with supernovae energy output. Watch this space!