Andreas Tersenov

PhD candidate in Cosmology / Astrostatistics at the Institute of Computer Science and the Institute of Astrophysics, FORTH in Greece, and at the CosmoStat lab of CEA Saclay in France.

I’m a PhD student in cosmology with a background in theoretical physics, machine learning, and statistical inference, under the supervision of Jean-Luc Starck and Martin Kilbinger. My research focuses on understanding the large-scale structure of the Universe through the effect of weak gravitational lensing, using simulation-based inference, mass mapping techniques, higher-order statistics, and probabilistic machine learning models.

I am currently a member of the TITAN project, an EU ERA Chair program on AI and its applications in Astrophysics. I am also a member of the Euclid and UNIONS Cosmological Surveys. At the moment, I am working on improving how we reconstruct the dark matter distribution from lensing data, implementing higher-order statistics and probabilistic machine learning models to derive constraints on the cosmological model parameters.

Before starting my PhD, I received a Master’s degree in Astrophysics and Space Physics from the University of Crete, in Greece, where I first started working in data-driven cosmology. Prior to that, I studied physics, and had the chance to work on diverse topics—from Ultra-High Energy Cosmic Rays to Holographic Renormalization Group Flows and the Anti-de Sitter/Conformal Field Theory correspondence.

Beyond research, I organize and teach at the Astrostatistics Summer School in Crete, and contribute to open‑source cosmology software. If you’re curious about my research, collaborations, or just want to chat about cosmology and AI, feel free to reach out.