Ronaldas Macas
Data scientist developing machine learning and generative AI solutions in financial technology, with expertise in time-series analysis, signal processing, and statistical modeling. Previously searched for exploding stars using the most sensitive instrument in the world.
- Revisiting the evidence for precession in GW200129 with machine learning noise mitigation —
- Quasi-physical model for removing short glitches from LIGO and Virgo data —
- A sensitive test of non-Gaussianity in gravitational-wave detector data —
- Impact of noise transients on low latency gravitational-wave event localisation —
- Bayesian inference analysis of unmodelled gravitational-wave transients —