The #LISACommunity recently hosted a talk by Senwen Deng on a paper by Senwen Deng, Stanislav Babak, Maude Le Jeune, Sylvain Marsat, Éric Plagnol, Andrea Sartirana: "Modular global-fit pipeline for LISA data analysis", linked here 
https://arxiv.org/abs/2501.10277
Here's a summary of the paper:
"The #LISAMission data band is expected to be dominated by gravitational wave signals emitted by a plethora of astrophysical sources. Signals of the Galactic white dwarf Binaries are long-lived, overlapping in time and their unresolved residual forms a confusion noise. Massive Black Hole Binary signals are loud and broadband, hindering the estimation of the noise property, the knowledge of which is key to the detection and parameter estimation for the gravitational wave signals. We came up with a modular two-stage iterative pipeline prototype to disentangle the intertwined signals and to infer the parameters for the different signal sources and the noise level. We demonstrated its capability by applying it to simulated LISA dataset known as "Sangria", where we managed to recover the injected parameters at the simulation with faithfulness."
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