UPSILoN (AUtomated Classification of Periodic Variable Stars using MachIne LearNing) classifies periodic variable stars such as Delta Scuti stars, RR Lyraes, Cepheids, Type II Cepheids, eclipsing binaries, and long-period variables (i.e. superclasses), and their subclasses (e.g. RR Lyrae ab, c, d, and e types) using well-sampled light curves from any astronomical time-series surveys in optical bands regardless of their survey-specific characteristics such as color, magnitude, and sampling rate. UPSILoN consists of two parts, one which extracts variability features from a light curve, and another which classifies a light curve, and returns extracted features, a predicted class, and a class probability. In principle, UPSILoN can classify any light curves having arbitrary number of data points, but using light curves with more than ~80 data points provides the best classification quality.

ASTRiDE detects streaks in astronomical images using a "border" of each object (i.e. "boundary-tracing" or "contour-tracing") and their morphological parameters. Fast moving objects such as meteors, satellites, near-Earth objects (NEOs), or even cosmic rays can leave streak-like traces in the images; ASTRiDE can detect not only long streaks but also relatively short or curved streaks.

PDT removes systematic trends in light curves. It finds clusters of light curves that are highly correlated using machine learning, constructs one master trend per cluster and detrends an individual light curve using the constructed master trends by minimizing residuals while constraining coefficients to be positive.

SPISEA (Stellar Population Interface for Stellar Evolution and Atmospheres) generates single-age, single-metallicity populations (i.e., star clusters). The software (formerly called PyPopStar) provides control over different parameters, including cluster characteristics (age, metallicity, mass, distance); total extinction, differential extinction, and extinction law; stellar evolution and atmosphere models; stellar multiplicity and Initial Mass Function; and photometric filters. SPISEA can be used to create a cluster isochrone in many filters using different stellar models, generate a star cluster at any age with an unusual IMF and unresolved multiplicity, and make a spectrum of a star cluster in integrated light.