Me in a few words
I am Adrien Anthore; 2nd year Master’s student at the Paris Observatory - PSL; Content creator for L’Observatoire d’Adrien; Amateur astronomer.
Bio
I’m Adrien Anthore, an astrophysics student and amateur astronomer. I graduated from the Physics Intensive Track at Sorbonne University (2022), SPRINT (Sorbonne Physics Research Intensive and New Technologies), and I will soon graduate from the Astrophysics Graduate Programme at the Paris Observatory - PSL (2024), in IRT (International Research Track), majoring in Observational Astrophysics.
Since 2021, I have been actively involved in science communication and popularisation. I am committed to sharing my knowledge and raising public awareness of the importance of scientific research and the challenges it faces. It is in this spirit that I have created this programme: L’Observatoire d’Adrien, a programme to popularise astrophysical topics on the Internet. In addition to my online activities, I regularly participate as a speaker in scientific congresses or festivals open to the general public, such as the Explor’Espace festival in 2021 or the “Fête de la Science” in universities since 2022. I also intervene in the school environment, mainly to discuss scientific studies and career prospects.
As a child, I discovered astronomy through books and by observing the stars at night.
I wanted to continue observing, first using binoculars to look at the moon and the planets.
Then I started to buy instruments to observe more and more objects.
Today I have a 200/1200 Dobson, a 70/700 refractor and an electronically assisted instrument.
The images I take are mostly from my EA, but also from Lucky Imaging.
I also make observational drawings.
If you are interested in my work and would like me to participate in an event you are organising, whether for school or other purposes, please contact me with details of your project. I will be happy to help and offer my services.
Send a mail here
Center of interest
Astrophysics/Astronomy; Radioastronomy; Interferometry; Galaxies; Machine-Learning & Deep Learning; Observations; Popular Science; Open Science.