32 citations · 70 across the 12 of their papers we have counts for
13 papers
Solar Wind Classifications at Mars using Machine Learning Techniques
Catherine E. Regan, Silvia Ferro, Austin M. Smith +5
Understanding solar wind variability throughout the heliosphere is essential for fundamental space physics and future exploration of the Moon and Mars. The Mars Atmosphere and Vola…
A Search for Exoplanet Candidates in TESS 2-min Light Curves using Joint Bayesian Detection
Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
In this work, we apply an exploratory joint Bayesian transit detector (Taaki et al. 2020), previously evaluated using Kepler data, to the 2 min simple aperture photometry light cur…
Robust Detrending of Spatially Correlated Systematics in Kepler Light Curves Using Low-Rank Methods
Jamila Taaki, Athol Kemball, Farzad Kamalabadi
Light curves produced by wide-field exoplanet transit surveys such as CoRoT, Kepler, and TESS are affected by sensor-wide systematic noise which is correlated both spatiotemporally…
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting
Helmuth Naumer, Farzad Kamalabadi
This work introduces a method to select linear functional measurements of a vector-valued time series optimized for forecasting distant time-horizons. By formulating and solving th…
Low SNR Multiframe Registration for Cubesats
Evan Widloski, Farzad Kamalabadi
We present a registration algorithm which jointly estimates motion and the ground truth image from a set of noisy frames under rigid, constant translation. The algorithm is non-ite…
Spatial-temporal switching estimators for imaging locally concentrated dynamics
Parisa Karimi, Mark Butala, Zhizhen Zhao +1
The evolution of images with physics-based dynamics is often spatially localized and nonlinear. A switching linear dynamic system (SLDS) is a natural model under which to pose such…
Quantification of mismatch error in randomly switching linear state-space models
Parisa Karimi, Zhizhen Zhao, Mark Butala +1
Switching Kalman Filters (SKF) are well known for their ability to solve the piecewise linear dynamic system estimation problem using the standard Kalman Filter (KF). Practical SKF…
Efficient model selection in switching linear dynamic systems by graph clustering
Parisa Karimi, Mark Butala, Zhizhen Zhao +1
The computation required for a switching Kalman Filter (SKF) increases exponentially with the number of system operation modes. In this paper, a computationally tractable graph rep…
High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction
Figen S. Oktem, Oğuzhan Fatih Kar, Can Deniz Bezek +1
Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral reso…
Optimal Measurement Configuration in Computational Diffractive Imaging
Evan Widloski, Ulas Kamaci, Farzad Kamalabadi
Diffractive lenses have recently been applied to the domain of multispectral imaging in the X-ray and UV regimes where they can achieve very high resolution as compared to reflecti…
Bayesian Methods for Joint Exoplanet Transit Detection and Systematic Noise Characterization
Jamila Taaki, Farzad Kamalabadi, Athol J. Kemball
The treatment of systematic noise is a significant aspect of transit exoplanet data processing due to the signal strength of systematic noise relative to a transit signal. Typicall…
Roadmap for Reliable Ensemble Forecasting of the Sun-Earth System
Gelu Nita, Rafal Angryk, Berkay Aydin +44
The authors of this report met on 28-30 March 2018 at the New Jersey Institute of Technology, Newark, New Jersey, for a 3-day workshop that brought together a group of data provide…
Time-Dependent Reconstruction of Non-Stationary Objects with Tomographic or Interferometric Measurements
R. A. Frazin, M. D. Butala, A. Kemball +1
In a number of astrophysical applications one tries to determine the two-dimensional or three-dimensional structure of an object from a time series of measurements. While most meth…