Researchers

My research program focuses on studying time domain, large survey astronomy, with an emphasis on magnetically active stars in surveys like Kepler and TESS, and future missions including ZTF and LSST.

  As a post-bacc working with the VPL, I have a general interest in all things astrobiology with a soft spot for habitablity and biosignatures. My current research consists of coupling 3D general circulation models and 1D radiative transfer models to simulate and visualize spatially variant exoplanet atmospheres, and simulating how varying levels of incident UV radiaiton from M-dwarf stars affect the atmospheres of exoplanets that orbit them.  

I am a software developer working on problems at the intersection of software engineering, science, and statistics. I currently work on the Large Synoptic Survey Telescope’s alert production pipeline, a complex framework for turning LSST’s flood of raw data into a flood of science within 60 seconds. I’m involved in a variety of projects for the pipeline, including developer infrastructure, objects and interfaces for managing astronomical coordinate transformations, and a fail-resistant framework for pipeline verification.

I currently work with the LSST Data Management team as a Project Science Analyst. My main research focus is supernovae, especially those of Type Ia.

Planetary atmospheres and dynamics of exoplanets. Applying machine learning to large astronomical data sets.

Daniela Huppenkothen is the Associate Director at the Institute for Data-Intensive Research in Astrophysics and Cosmology (DIRAC) at the University of Washington and a Data Science Fellow at the University of Washington’s eScience Institute, where she works on astrostatistics for astronomical time series, and is interested in everything from asteroids to black holes. She is excited about teaching data science to astronomers and researchers from other scientific disciplines, and about finding new ways to get researchers across different scientific domains to talk to one another. Previously, she was a Moore-Sloan Data Science Postdoctoral Fellow at New York University, and a PhD student at the University of Amsterdam.

Coming soon!

Coming soon!

I am an optical/mechanical engineer working primarily for Apache Point Observatory. I am designing new instrumentation and working on other improvements to the telescopes.

I currently work as a software and algorithm developer on the Large Synoptic Survey Telescope (LSST) as part of the Data Management, Alert Production team at UW. My main interests are in the field of cosmology specifically weak gravitational lensing and large-scale structure and using these measurements to constrain the dark sector of the Universe. I am also involved in the LSST Dark Energy Science Collaboration (DESC) developing methods to estimate galaxy redshifts from galaxy clustering statistics.

I am a software developer working on data processing software for the LSST project. I also spent many years working on control software for Apache Point Observatory.

I started mining data in SDSS, and am now am digging in the LSST codebase, looking for beautiful gems of transient knowledge as part of the UW LSST Alerts Production team. Our goal: to find all the things that go bump in the night. Prior to this, I  measured galaxy clustering in SDSS and BOSS, and studied galaxies and the black holes that love them for my thesis.

I work with the Large Synoptic Survey Telescope (LSST) Data Management group to develop software for Alert Production. The Alert Production Pipeline does image processing, image differencing, and source association to find real astrophysical objects that have changed brightness or position in the sky and alert the community in near-real-time. I’m also a researcher in stellar astronomy with a focus on binary and variable stars.

I work on understanding interactions between the Milky Way and the population of dwarf galaxies in the Local Group. This includes observing the tidal debris left behind by dwarfs as they fall onto the Galaxy, along with modeling the changing properties of dwarfs as they become satellites of the Milky Way. Much of my work uses data from the Pan-STARRS survey. I am part of the LSST Data Management System Science Team, and I support that project with analyses of the scientific requirements and expected  performance of the survey.

Jennifer is a participant in the Sloan Digital Sky Survey (SDSS) and serves as the Project Manager for one of its cornerstone projects, the Apache Point Galactic Evolution Experiment 2 (APOGEE-2).  Her research is centered on the chemical composition of stellar populations as well as the chemical evolution of various Galactic components. She is also interested in stellar astrophysics and the use of fundamental physics data to improve the derivation of stellar parameters. As a member of a large-scale data project, Jennifer is keen to develop efficient data extraction and utilization techniques.  She also attempts to search for patterns and correlations in data.

I work for the APOGEE south survey on the infrastructure side of things. For information on the survey visit the SDSS website.

Peter Yoachim is a staff scientist working with LSST on issues of telescope scheduler optimization and calibration.  Scientifically, I work on galaxy formation and evolution, particularly using IFU observations to measure galaxy dynamics and star formation histories.