Jonathan is a support scientist working on the James Webb Space Telescope Near-InfraRed Imager and Slitless Spectrograph (NIRISS) and the Near InfraRed Camera (NIRCam). He develops both high-level calibraiton pipelines and prediction engines for time series observations. His research is focused on exoplanet atmospheric abundances.
Jonathan is particularly fascinated with applying advanced machine learning algorithms to astrophysical data: deep neural networks, random forests, clustering, classification, and regression techniques.
- JWST calibration for NIR time series observations
- Exoplanet atmospheric abundance measurements
- Predictions for exoplanet atmospheric measurements with JWST
- Analyzing phase curve observations of exoplanets with Spitzer
- Analyzing transmission and emission spectroscopy of exoplanets with Hubble-WFC3
- Developing a deep neural network to detect small planets with Kepler, K2, and TESS
- Advanced machine learning algorithms
- Applying data science techniques to astrophysical observations
Research Topics: JWST, NIRISS, NIRCam, Infrared, Instrumentation, Exoplanets, Detection, Planet Formation, Atmospheres