I build scientific Python software, ideally with PyTorch/JAX, focusing on interpretability, flexibility, uncertainty, and impact.
- blasรฉ: Interpretable Machine Learning for super-resolution semi-empirical spectroscopy in PyTorch and JAX (paper)
- gollum: Python API to precomputed synthetic spectral models
- muler: Python API to รฉchelle spectra from IGRINS, HPF, and Keck NIRSPEC (paper)
- ynot: A spectrograph digital twin for pixel-perfect รฉchellogram forward modeling in PyTorch (paper draft)
- lightkurve: Python API for precision time series photometry from Kepler/K2/TESS
- Starfish: Robust likelihood function for astronomical spectral inference
- A Large and Variable Leading Tail of Helium in a Hot Saturn Undergoing Runaway Inflation (paper, code)
- Observationally Constraining the Starspot Properties of Magnetically Active M67 Sub-subgiant S1063 (paper, code)
- Placing the Spotted T Tauri Star LkCa 4 on an HR Diagram (paper, code)
- Optical characterization of gaps in directly bonded Si compound optics using infrared spectroscopy (paper, code)
- My PhD Thesis at UT Austin Astronomy (dissertation, revision history)
Starspots: contracosta, acdc, ๐monhegan, ๐ star-witness, ๐hopful, ๐ calico, xveganx, ๐ KaneDoe, ๐ varasly
Brown Dwarfs: ๐gandules, varsity, ๐ lombok, ๐ ucdwhpf, jammer, ๐ BAADE, ๐zoja
Methodological: coldrum (ft. pysr), fiatlux, TgiF, HelloWorldNet, gpytorch-astro, ffi-motion, bombcat, probabilisticAGN
Hardware: nubble, postale