My favourite tool to do this is Asteroseismology. In this research field seismic techniques are applied to the brightness variations of pulsating stars to derive their structure and various fundamental parameters. I am mainly interested in the analysis and modeling of observed frequency spectra, with special attention to opacity-driven pulsators such as Scuti stars.
Scuti stars are more massive than the sun, with approximately 1.5 to 2.5 solar masses and situated in the classical instability strip. Both the large number of pulsation modes and their mixed acoustic and gravity properties provide excellent prospects to study the stellar interior. At the same time the high number of observed frequencies complicates the pattern recognition (e.g., the association of observed frequencies to modes of specific surface geometry, defined by spherical harmonics).
Within this context I am also focussing on the development of software tools. The most popular of these tools, Period04 (http://www.univie.ac.at/tops/period04), is a software for the analysis of time series of brightness variations containing observational gaps.
Within the last years vast amounts of satellite data have become available. These data pose an interesting algorithmic playground. Currently, I am interested in the application of deep learning techniques for the recognition of certain patterns in the stellar light curves.
Contact Patrick at patrick.lenz@(NO_SPAM)ronininstitute.org