My research interests are primarily in dark matter, gravity, gravitational lens detection and modeling, and advanced tools for accessing, reducing and analyzing data. I am the head of data management and archiving for the Sloan Digital Science Survey (SDSS), and I serve as the primary SDSS data scientist responsible for the SDSS science archive, centered at the University of Utah, which is the primary site for the survey’s data processing pipelines and web application hosting.

Joel Brownstein
Dr. Joel R. Brownstein
Research Associate Professor

Research Topics

Strong Gravitation Lensing
My research includes the spectroscopic detection of strong galaxy graviational lenses, and their followup imaging, and lens modeling.
Dark Matter
I am most interested in the shape of dark matter profiles within galaxies, as measured from probes such as strong gravitational lens models and galaxy rotation curves, and their dissection into luminous and dark components.
Galaxy Clustering and Evolution
I work to understand the large-scale structure of the Universe, including the clustering and evolution of galaxies, and I am particularly interested in the amount of stellar mass – as measured from stellar population synthesis models, and the dynamic (total) mass – measured from the velocity dispersions.
There is no greater mystery in physics, than the force of gravity beyond Einstein's theory. I am most interested in the emergence of space-time from a more fundamental sub-structure, and the renormalization sector of quantum gravity, and possible massive fields that would generate a Yukawa-type fifth force, breaking the equivalence principle at astrophysical distances, and providing a modified gravity alternative to dark matter.
I am most interested in the relationship between the dark energy field in ΛCDM and Einstein's cosmological constant, particularly the possibility that renormalization of λ could have measurable predictions when compared to data from strong gravitational lensing.

Computational Tools

Although I am expert in a number of object-oriented computer languages with more than 20 years of scientific programming experience, python3 is my current laguage of choice, for its ease of readability and maintainability which allows me to code more rapidly and more robustly. The vast number of available open source packages makes this language highly optimized for astronomical computation, including database-driven software, web application development, graphical user interface, and new approaches to data science which leverage modern machine learning.
I have been using databases in my scientific computation for more than 20 years, particularly to add persistence and transparency to my work. I use SQLAlchemy models to abstract and maintain physical quantities in each of my computations.
Docker Machines
Portability is essential when working in scientific collaborations. I use docker machines to embed my scientific software, and particularly my web applications, mininizing the effort required to install software on new hardware and to distribute software without complications caused by software dependency management.
Flask Web Apps
This lightweight framework is an extremely powerful tool to rapidly generate web applications and server-side API. I currently use bootstrap and jquery to make the client a more efficient and more useable interace for my applications.

Astronomical Data

I have a number of funded projects related to each of the SDSS-V Mappers, including both data analysis (intended for research publications) and data visualization (for webapp and api development) and data software frameworks (to prepare for future data releases).
I am currently working on the final data release for SDSS-IV, including a number of value-added catalogs related to the Spectroscopic Identification of Lensing Objects (SILO) and other data analysis projects (with research publications currently in preparation), updating the Science Archive Webapp for the data release, and managing the SDSS-IV science archive server, which includes a variety of systems managed by the Utah Center for High Performance Computing (CHPC).
I contributed as a postdoc to the development of the SDSS-III BOSS pipeline for each SDSS-III data release including the final one (DR12). I was particularly interested in ensuring that the final reductions were of sufficient quality to be optimal for the search for background galaxies as part of the strong gravitational lensing detection project -- the BOSS emission-line lensing search (BELLS), and I was responsible for the implementation of the BOSS galaxy product, which computes a variety of galaxy parameters including stellar masses for each galaxy with a good spectrum.
I was co-Investigator on a number of HST proposals to observe strong gravitational lenses detected in SDSS-III (SLACS) and SDSS-IV (BELLS), which led to a number of publications. There are significant challenges remaining in the data analysis in order to dissect these galaxies in luminous and dark components, and there are new candidates from SDSS-IV (SILO) that are ideal for followup HST imaging.
For my Ph.D. work, I created 36 high resolution galaxy rotation curves using the Spitzer I-band for spiral galaxies in the Ursa Major (UMa) filament, and dissected the components into stellar, gaseous, and modelled both the dark matter components using both the NFW profile, and a core-modified dark matter profile, and compared these results to the alternative provided by Modified Gravity (MoG) and Modified Newtonian Dynamics (MOND).

Scientific Activity

My publications listed here, with statistics.
My talks listed here, with slides.
A list of my current and previous committee work.
A list of my professional affiliations.