Ingo Waldmann


Department of Physics & Astronomy
University College London

Curriculum Vitae
PhD Thesis
ORCID
ResearchGate

Hi, that's me. I'm a post-doctoral researcher at the Unversity College London working in the field of extrasolar planet characterisation. I specialise in the data analysis and atmospheric modelling of exoplanet atmospheres. Exoplanets are planets that orbit other stars. When one of these planets happens to pass between its host star and us, some of the star's light filters through the atmosphere of that plannet. Now that is a tiny amount and extremely hard to detect with our current technology. For this reason, I focused my PhD thesis (available here) on using machine learing techniques to 'learn' how to best mine for those tiny planetary signals hidden within the noise of the instrument and star. Together with my students and collaborators, we have continued developing these algorithms and have recently won the Spitzer Space Telescope Data Challenge (paper here) as the most reliable and accurate algorithm.

More recently, togetehr with my student turned colleague, Marco Rocchetto, I have focused more on the theoretical modelling of the atmospheres of these planets. In particular on the question: What can we learn from current and future observations? How do they constrain our knowledge of the atmospheric chemistry and temperatures?
To answer these questions, we developed the Tau-REx retrieval framework (for more info, have a look at the projects page. In many ways this is the field leading software to analysing atmospheric spectra of exoplanets and we are developing this framework with modern deep learning techniques in mind. Here deep learning can help

Generally regarding this website. This is a work in progress. I want to provide an archive of our recent open-source codes (they are on GitHub but an overview is needed) and data here. Also some code-documentation and a messaging board for code-related questions is planned. And finally I want to put some more photos up in a gallary... let's see!