Marko Ristić
Schmidt AI in Science Fellow · APS Career Mentoring FellowUC San Diego
My research focuses on studying neutron star mergers and the neutron-rich material that they eject. I develop pioneering radiative transfer simulations and machine learning emulators to study kilonovae, the radioactively-powered electromagnetic transients following neutron star mergers.
Research interests
- Neutron star mergers
- Kilonovae
- Radiative transfer
- Machine-learning emulators
- r-process nucleosynthesis
- Multi-messenger inference
Recent papers
All 17 publications →- ASTRAL: A Framework for Optimal Placement and Emulation of Stellar Evolution Models Gravely et al. · Preprint · Oct 2026
- A Comparison of Three Neodymium Atomic Data Sets for Kilonova Modeling Fontes et al. · ApJ · May 2026
- Joint electromagnetic and gravitational wave inference of binary neutron star merger GW170817 using forward-modeling ejecta predictions Ristić et al. · Phys. Rev. Research · May 2026 First author