BRINGING SPACE EXPLORATION AI APPLICATIONS BACK TO EARTH Machine Learning for Exoplanet research Lessons and results from NASA Frontier Development Lab

Jul 30, 2019 - 11:00 am to 12:00 pm

Campus, Varian 355

Daniel Angerhausen (Bern University)

Abstract:  I will present results from NASA's Frontier Development Lab 2018, an Artificial Intelligence/Machine Learning incubator tackling challenges in the Exoplanet and Astrobiology fields, such as planet search in TESS data or retrieval of exoplanet spectra. A particular focus will be on two data sets produced at FDL 2018: a set of 3 million exoplanet spectra calculated with the GSFC Planetary Spectrum Generator (PSG) and a set of 150.000 exoplanet atmospheres computed with the ATMOS code.


Dr. Daniel Angerhausen is an Astrophysicist and Astrobiologist at the Center for Space and Habitability at Bern University. The former NASA postdoctoral fellow is also founder and CEO of the Science and Tech Communication start-up 'Explainables', a diverse team of highly qualified young communicators from all over the globe. On his search for planets around other stars Daniel already flew five missions on the NASA airborne telescope SOFIA. Daniel is also mentor and science committee member of NASA Frontier Development Lab, an Artificial Intelligence/Machine Learning incubator tackling challenges in various fields of space sciences in collaboration with industry stakeholders such as Google Cloud, Nvidia or IBM. Daniel plays Sepaktakraw, an artistic footvolleyball game and competed several times at World Championships in South East Asia. //