My research focuses on understanding dark matter and its influence on galaxy formation/evolution in the context of our own Galaxy. I am particularly interested in modeling and quantifying the asymmetric distribution of dark matter in the Milky Way by building tailored tools that can work in the disequilibrium regime and zoomed hydrodynamical cosmological simulations of the Milky Way-mass galaxies. I use systems such as stellar streams–disrupted satellite galaxies–as a probe for DM. I am also interested in alternative dark matter models, specifically self-interacting dark matter and its effects at galactic scales.

I am interested in learning about the nature of dark matter and galaxy formation using wide-field astronomical surveys such as the Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory.
In particular, I work on finding and characterizing stellar streams and dwarf galaxies in the local universe and enabling this science by making infrastructure level contributions to cosmological surveys. These contributions range from instrumentation and calibration to science validation and software development. At the University of Washington I am a DiRAC postdoctoral fellow as well as a fellow in the eScience institute. Previously, I was a postdoc at another UW on an isthmus (University of Wisconsin-Madison) where I was part of the observational cosmology group, and I completed my PhD at Texas A&M University.

I am an LSST-DA Catalyst Prize Fellow and am currently hosting my fellowship at the DiRAC Institute. I use the latest advances in machine learning combined with large surveys to study the formation & evolution of galaxies and investigate the specific role played by Active Galactic Nuclei in this process.

Please take a look at my website to learn more about my research! 

I am a postdoctoral scholar with a dual appointment; half the time working on LSST commissioning and half of the time serving as an Associate Director for LINCC Commissioning. My previous software development experience is as a pipeline specialist for the Prime Focus Spectrograph, the flagship instrument for the Subaru telescope. My research focus is extragalactic time-domain science, stochastic models of star-formation, and galaxy-black hole evolution. My main interest is the optical variability of active galactic nuclei, where I use large datasets and advanced statistical methods to determine the connections between variability and physical parameters driving this variability. 

Samuel Wyatt is a Postdoctoral Scholar for the LINCC Frameworks commissioning whose research interests are heavily tied to observational transient research and big-data in astronomy. Most of his PhD research was spent developing robotic telescope capabilities for the small telescopes (<2m) at the University of Arizona with the anticipation of automated follow-up of interesting LSST discoveries. He is also passionate about efforts in discovering gravitational wave counterparts through his work in developing the Gravitational Wave Treasure Map [treasuremap.space], which is designed to enable coordination between observatories in order to minimize unnecessary overlap in these searches and find the counterpart as quickly and as efficiently as possible.

Outside of astronomy he enjoys long rides on his bicycle, and yelling into the mediocre abyss that is the Nashville Predators ice hockey team.

I completed my Ph.D at the University of Pennsylvania, focusing on the development and application of new techniques for the discovery and characterization of the most distant bodies in our Solar System, trans-Neptunian objects, as part of the Dark Energy Survey (DES). At the University of Washington, I am expanding this research to current surveys, as well as upcoming projects such as the Rubin Observatory’s Legacy Survey of Space and Time (LSST).
Discovering these objects is inherently a computationally expensive task, requiring these bodies to be tracked across multiple telescope images during several years of observations, as these move against the background of stars in the night sky. My research focuses on the development of computationally efficient and effective algorithms to enable such discoveries. I am also interested in the relationship between models of formation of the Solar System and the population of trans-Neptunian bodies, and I am carrying studies of photometric colors as well as comparisons of theoretical populations to observed data.

Born in Poland, graduated with MPhys Physics in 2012 (University of Oxford), obtained a PhD in Astronomy and Astrophysics in 2019 (University of Washington). Pursuing research in Astrophysics, specializing in the analysis of time series data, using the variability information to classify and characterize quasars and variable stars. Since 2020 working within the Active Optics System group as a commissioning postdoc for the Rubin Observatory (LSST).

Joachim Moeyens is a Postdoctoral Fellow at the DiRAC Institute at the University of Washington. He is interested in big data and software driven solutions to problems in astronomy. During his undergraduate studies at the University of Washington, he was presented with the opportunity to work on a research project for the Vera Rubin Observatory’s Legacy Survey of Space and Time (LSST).  For his doctoral thesis, Joachim is working on algorithms that discover minor planets in astronomical surveys, in particular, on Rubin Observatory’s Solar System Processing pipelines, and on a novel algorithm named Tracklet-less Heliocentric Orbit Recovery (THOR).