Future space-based laser interferometric detectors will be able to observe gravitational waves (GWs) generated during the inspiral phase of stellar-mass binary black holes (SmBBHs), which contain a wealth of important physical information concerning astrophysical formation channels and fundamental physics constraints. However, the detection and characterization of GWs from these SmBBHs remains one of the major challenges in data analysis. In this work, we construct a data analysis pipeline using the semi-coherence method and Particle Swarm Optimization (PSO), while accelerating the analysis using the frequency domain response of the detector and parallel computation based on the Graphics Processing Unit (GPU). As a result, we can perform global searches for the GW signals of SmBBH and estimate the parameters in a reasonable time for the simulated data for the Laser Interferometer Space Antenna (LISA). We test the performance of our pipeline on simulated data sets containing realistic noise and demonstrate that, for GW signals with signal-to-noise ratios (SNRs) in the range of 15 to 20, LISA can accurately determine most of the parameters, including the orbital eccentricity. In this talk, we will present the fundamentals of our pipeline, its implementation and robustness, and provide new insights into the future of space-based GW detection and parameter estimation.