Anais Möller

supernovae | time-domain astronomy | cosmology | machine learning

I am driven to understand the nature of Dark Energy and the physics of transients in the Universe. To do so, I work with extremely large astronomical datasets. To maximize the information we can use to understand our Universe, I develop innovative tools with a large emphasis on machine learning.

Research interests:

  • I am co-leading Fink broker which will process, enrich and filter transient data from the largest optical survey in the world at the Vera C. Rubin Observatory.
  • I obtain constraints on the nature of Dark Energy with Type Ia Supernovae at the Dark Energy Survey.
  • I study multi-wavelength and messenger fast-transients with the world’s largest transient collaboration the Deeper Wider Faster program.
  • I am an Associate Investigator at the ARC Centre of Excellence for Gravitational Wave Discovery where I work on the optical and multi-wavelength follow-up of gravitational waves events.
  • I develop high-end machine learning algorithms for astronomy and cosmology such as the photometric classification framework SuperNNova.

I am currently a Postdoctoral Research Fellow at Swinburne University Centre for Astrophysics and Supercomputing in Australia. I previously worked for CNRS at Laboratoire de Physique de Clermont (LPC), and at the Australian National University as an ARC CoE CAASTRO Postdoctoral Fellow in Dark Energy.

I was born in Venezuela and did my undergrad at Universidad Simón Bolívar. I then moved to France and did the NPAC master and a PhD at Irfu Cea Saclay and Université Paris Diderot. I enjoy communicating science and was selected to be a CAASTRO Astronomer in Residence at Uluru, Australia. I speak spanish, english, french and german. I also ejoy hiking, rock climbing, diving, sailing and playing cello.


Sep 1, 2021 New job alert ! I have joined the Swinburne University Centre for Astrophysics and Supercomputing as Postdoctoral Research Fellow.
Aug 13, 2021 Fink has been selected to process the Vera C. Rubin Observatory LSST alert stream for its 10-years of operation. Fink will enable transient science in this big data era, including SNe Ia cosmology and beyond!

selected publications

  1. The Dark Energy Survey 5-year photometrically identified Type Ia Supernovae
    Möller, A., Smith, M., Sako, M., Sullivan, M., Vincenzi, M., and Wiseman, et al.
    arXiv e-prints Jan 2022
  2. Fink: early supernovae Ia classification using active learning
    Leoni, Marco, Ishida, Emille E. O., Peloton, Julien, and Möller, Anais
    arXiv e-prints Nov 2021
  3. The Dark Energy Survey Supernova Program: Cosmological biases from supernova photometric classification
    Vincenzi, M., Sullivan, M., and Möller, et al.
    arXiv e-prints Nov 2021