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Eclipsing binaries (EBs) provide critical laboratories for empirically testing predictions of theoretical models of stellar structure and evolution. Pre-main-sequence (PMS) EBs are particularly valuable, both due to their rarity and the…
We present the results of our spectroscopic observations of eight detached eclipsing binaries (DEBs), selected from the $Kepler$ Eclipsing Binary Catalog. Radial velocities (RVs) were calculated from high resolution spectra obtained with…
In the last couple of decades, tremendous progress has been achieved in developing robotic telescopes and, as a result, sky surveys (both terrestrial and space) have become the source of a substantial amount of new observational data. These…
I derive the physical properties of 30 transiting extrasolar planetary systems using a homogeneous analysis of published data. The light curves are modelled with the JKTEBOP code, with attention paid to limb darkening and eccentricity. The…
Semidetached binaries, distinguished by their mass transfer phase, play a crucial role in elucidating the physics of mass transfer within interacting binary systems. To identify these systems in eclipsing binary light curves provided by…
We introduce a new machine learning based technique to detect exoplanets using the transit method. Machine learning and deep learning techniques have proven to be broadly applicable in various scientific research areas. We aim to exploit…
We describe a new neural-net based light curve classifier and provide it with documentation as a ready-to-use tool for the community. While optimized for identification and classification of eclipsing binary stars, the classifier is general…
Eclipsing binaries are important benchmark objects to test and calibrate stellar structure and evolution models. This is especially true for binaries with a fully convective M-dwarf component for which direct measurements of these stars'…
The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ~75% of the sky throughout its two year primary mission, resulting in millions of TESS 30-minute cadence light curves to analyze in the search for…
The TESS mission produces a large amount of time series data, only a small fraction of which contain detectable exoplanetary transit signals. Deep learning techniques such as neural networks have proved effective at differentiating…
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…
Full tests to stellar models below 1 Msun have been hindered until now by the scarce number of precise measurements of the stars' most fundamental parameters: their masses and radii. With the current observational techniques, the required…
The Comprehensive Research with Echelles on the Most interesting Eclipsing binaries (CR\'EME) projects was aimed to collect high-resolutions spectra of about 380 detached eclipsing binaries (DEBs), which mostly do not have literature RV…
We present a systematic phase curve analysis of known transiting systems observed by the Transiting Exoplanet Survey Satellite (TESS) during year one of the primary mission. Using theoretical predictions for the amplitude of the planetary…
Targeted observations of possible exomoon host systems will remain difficult to obtain and time-consuming to analyze in the foreseeable future. As such, time-domain surveys such as Kepler, K2 and TESS will continue to play a critical role…
We carried out a systematic study of full-orbit phase curves for known transiting systems in the northern ecliptic sky that were observed during Year 2 of the TESS primary mission. We applied the same methodology for target selection, data…
This study presents a multi-task machine learning framework for simultaneous morphology classification and physical parameter estimation of eclipsing binaries using photometric light curves. We train Random Forest and XGBoost ensemble…
The transit method allows the detection and characterization of planetary systems by analyzing stellar light curves. Convolutional neural networks appear to offer a viable solution for automating these analyses. In this research, two 1D…
A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we…
We identify 231 objects in the newly released Cycle 0 dataset from the Kepler Mission as double-eclipse, detached eclipsing binary systems with Teff < 5500 K and orbital periods shorter than ~32 days. We model each light curve using the…