Pedro Bernardinelli

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.

Chris Suberlak

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).

Bryce Kalmbach

I am a Postdoctoral Fellow at the DiRAC Institute and a UW Data Science Postdoctoral Fellow at the UW eScience Institute. I am a member of the Rubin Observatory Commissioning team as well as a member of two LSST Science Collaborations: the LSST Solar System Science Collaboration (LSST SSSC) and the LSST Dark Energy Science Collaboration (LSST DESC) where I am the co-convener of the Cosmological and Survey Simulations Working Group.

My scientific interests focus on creating new tools and methods to study large, complex datasets like the LSST through simulations, machine learning and high performance computing. These interests take me across a range of astronomical topics from detecting the faintest asteroids in our Solar System to measuring the distances to far-off galaxies.