- 👨🏻💻 Senior Software Engineer at the Space Telescope Science Institute, supporting JWST and Roman
- 🔭 Astronomer with interests in exoplanets, stellar activity, and statistical inference
- 🪐 Maintainer, Contributor, and Workshops Coordinator for astropy
- ⏰ Maintainer of the astropy-affiliated package for observation planning astroplan
- 🕸 http://brettmorr.is/
- 🎓 Curriculum Vitae
- 🆔 ORCID
- 📝 First author papers on NASA ADS
- astroplan (ApJ paper): Observation planning package for astronomers
- tynt: Light-weight astronomical color filter curves
- expecto: Retrieve PHOENIX model stellar spectra via FTP
- arcesetc (JOSS paper): Exposure time calculator for the ARC Echelle Spectrograph (ARCES) on the Apache Point Observatory 3.5 m Telescope
- aesop (JOSS paper): Echelle Spectroscopic Observation Pipeline for the ARC 3.5 m Telescope at APO
- stellarcmap: a matplotlib colormap for perceived colors from Gaia BP-RP
- kelp (Nature Astronomy paper, A&A paper I, A&A paper II): Photometric phase curves of exoplanets
- linea (A&A paper): Linear light curve detrending for CHEOPS
- robin (AJ paper): Robust exoplanet radii from ingress/egress durations
- stash (MNRAS paper, presentation): Simulate solar transits with observations from SDO HMI
- fleck (JOSS paper, ApJ paper, presentation): Fast approximate light curves for starspot rotational modulation
- gadfly: Simulate stellar oscillations and granulation with Gaussian processes
- hipparchos (AJ paper): Cross-correlation functions for high resolution spectroscopy
- jdaviz (presentation): JWST astronomical data analysis tools in the Jupyter platform
- romancal: Python library to process science observations from the Nancy Grace Roman Space Telescope
- lcviz: Light curve visualization and analysis tool
- shampoo (presentation): Digital holographic microscopy pipeline for astrobiology and beyond
- smitty: make LaTeX tables from posterior samples
- Introduction to JAX+numpyro for physical scientists
- Pareto smoothed importance sampling leave-one-out cross validation (presentation)
- How to compute leave-one-out cross validation stats for a numpyro (jax) model with a Gaussian process from celerite2
- Sample posteriors with SVI in numpyro
- Interactive MCMC demo
- Interactive Gaussian process demo
- Interactive Approximate Bayesian Computation demo
- Python for Astronomy Tutorial at Exeter (2019)
- Intro to Astropy Affiliated Packages at .Astronomy 9
- Linear model selection with PyMC3