NASA Ames AI/ML Seminar Series: Machine Learning for Exoplanet Vetting and Validation
Everyone is invited to the monthly artificial intelligence and machine learning virtual seminar hosted by the Exobiology Branch at the NASA Ames Research Center. Previously recorded seminars can be found on the AI-ML Astrobiology YouTube channel.
Time: March 17th, 12PM PDT/3PM EDT
The speaker for this event will be Dr. Hamed Valizadegan, a machine learning scientist at NASA Ames Research Center.
Title: Machine Learning for Exoplanet Vetting and Validation
Abstract: There has been growing interest in applying machine learning to vet transit signals from Kepler and TESS. Yet, adoption of these tools has faced inertia and resistance, partly due to limited understanding of machine learning foundations. Many in the astronomy, and particularly the exoplanet, community still favor traditional statistical methods such as Bayesian classifiers. In this talk, I will provide a brief overview of the history of machine classification, its Bayesian roots, and why deep learning has revolutionized automated analysis.
I will then introduce ExoMiner, a deep learning model developed in 2022 to classify transit signals and validate new exoplanets, along with its advanced successor, ExoMiner++, designed to vet TESS signals. I will also present performance results of these models on both Kepler and TESS data.
Astrobiology,
