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Biodiversity research requires complete and detailed information to study ecosystem dynamics at different scales. Employing data-driven methods like Machine Learning is getting traction in ecology and more specific biodiversity, offering…

Datasets in which measurements of two (or more) types are obtained from a common set of samples arise in many scientific applications. A common problem in the exploratory analysis of such data is to identify groups of features of different…

I measure and collect timings of phase markers (like eclipse times) for the orbits of 25 X-ray binaries (XRBs) so as to calculate the steady evolutionary period change ($\dot{P}$). I combine these with my observed $\dot{P}$ measures from 52…

We present a description of A dual-Beam pOlarimetric Robotic Aperture for the Sun (ABORAS), to serve as a Solar input with a dedicated Stokes V polarimeter for the HARPS3 high-resolution spectrograph. ABORAS has three main science drivers:…

Numerical N-body simulations are commonly used to explore stability regions around exoplanets, offering insights into the possible existence of satellites and ring systems. This study aims to utilize Machine Learning (ML) techniques to…

Machine learning techniques have been widely used in attempts to forecast several solar datasets. Most of these approaches employ supervised machine learning algorithms which are, in general, very data hungry. This hampers the attempts to…

For long-term simultaneous planning, localization and mapping (SPLAM), a robot should be able to continuously update its map according to the dynamic changes of the environment and the new areas explored. With limited onboard computation…

Measuring the magnetic field of the Milky Way reveals the structure and evolution of the galaxy. Pulsar rotation measures (RMs) provide a means to probe this Galactic magnetic field (GMF) in three dimensions. We use the largest…

Binary stellar evolution simulations are computationally expensive. Stellar population synthesis relies on these detailed evolution models at a fundamental level. Producing thousands of such models requires hundreds of CPU hours, but…

Machine Learning algorithms are good tools for both classification and prediction purposes. These algorithms can further be used for scientific discoveries from the enormous data being collected in our era. We present ways of discovering…

Recognizing already explored places (a.k.a. place recognition) is a fundamental task in Simultaneous Localization and Mapping (SLAM) to enable robot relocalization and loop closure detection. In topological SLAM the recognition takes place…

Long-term 3D map management is a fundamental capability required by a robot to reliably navigate in the non-stationary real-world. This paper develops open-source, modular, and readily available LiDAR-based lifelong mapping for urban sites.…

Solar image analysis relies on the detection of coronal holes for predicting disruptions to earth's magnetic field. The coronal holes act as sources of solar wind that can reach the earth. Thus, coronal holes are used in physical models for…

Variable stars, or particularly eclipsing binaries, are very essential astronomical occurrence. Surveys are the backbone of astronomy, and many discoveries of variable stars are the results of surveys. All-Sky Automated Survey (ASAS) is one…

Gravitational microlensing events are powerful tools for the study of stellar populations. In particular, they can be used to discover and study a variety of binary systems. A large number of binary lenses have already been found through…

We evaluate the modulation of Cosmic Microwave Background (CMB) polarization using a rapidly-rotating, half-wave plate (HWP) on the Atacama B-Mode Search (ABS). After demodulating the time-ordered-data (TOD), we find a significant reduction…

Here we greatly improve Artificial Intelligence (AI)-generated solar farside magnetograms using data sets of Solar Terrestrial Relations Observatory (STEREO) and Solar Dynamics Observatory (SDO). We modify our previous deep learning model…

The purpose of this letter is to address a blind-spot in our knowledge of solar active region statistics. To the best of our knowledge there are no published results showing the variation of the Mount Wilson magnetic classifications as a…

Black hole X-ray binary systems (BHBs) contain a close companion star accreting onto a stellar-mass black hole. A typical BHB undergoes transient outbursts during which it exhibits a sequence of long-lived spectral states, each of which is…

Recognizing a previously visited place, also known as place recognition (or loop closure detection) is the key towards fully autonomous mobile robots and self-driving vehicle navigation. Augmented with various Simultaneous Localization and…