About me

EWASS 2020, AI in astrophysics session

Contact: david.cornu@observatoiredeparis.psl.eu
My LinkedIn profile (with education and experience details)

I am a French numerical astrophysicist presently working as a postdoctoral researcher at Paris Observatory, University PSL (Paris Sciences Lettres) as a member of the LERMA (Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères) laboratory.

I mainly work on the development of state-of-the-art Machine Learning approaches and tools for the analysis of massive datasets from modern giant interferometers (LOFAR, ALMA, NenuFAR, MeerKAT, SKA, …), in the context of the MINERVA project.
I was the PI of the MINERVA team competing in the SKA Science Data Challenge 2, for which I developed a highly customized 3D-YOLO network. The MINERVA team won the first place of the challenge.
Press release and articles about the victory: SKAO (& Contact 9 pp16-17), CNRS, OBSPM, OCA, GENCI, ActuIA, and others …

Overall, I am interested in how ML methods can be used to solve existing and upcoming astrophysical problems, and in how the specific properties of astronomical datasets are challenging usual ML approaches.

Previous and present primary studies:
– Object detection, classification and parameter extraction in radio-astronomical
datasets using modern CNN architectures
– Extinction mapping of the Milky Way using CNNs
– Young Stellar Objects (YSOs) classification from Infrared surveys, mainly using ANNs

See my publications page.

For my studies, I developed a state-of-the-art Deep Learning framework called CIANNA (Convolutional Interactive Artificial Neural Networks by/for Astrophysicists), which is already competitive with widely adopted DL libraries (see Tools and Codes). CIANNA was my primary tool to work on the SKA SDC2.