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About

Giulia Pieramico is a rising star in the field of non-invasive brain stimulation, with her research primarily focused on advancing the precision and accessibility of transcranial magnetic stimulation (TMS). Her major contributions lie in developing novel, computationally-driven methods for targeting brain networks and creating open-source tools for closed-loop stimulation paradigms. Notably, her 2025 paper on "Targeting multi-locus TMS with Bayesian optimization" pioneers a data-driven approach to direct stimulation toward functionally relevant neural pathways, significantly improving the accuracy of dual-site TMS protocols. In parallel, her work on "NeuroSimo" introduces an open-source software platform that empowers researchers to rapidly prototype and implement closed-loop EEG- or TMS-guided experiments using a high-level programming language, breaking free from proprietary hardware constraints. While her most-cited papers currently hold 3 citations each, reflecting their very recent publication, their conceptual and practical importance is already clear. Pieramico’s work is poised to democratize advanced TMS methodologies, enabling more flexible, precise, and reproducible studies of brain connectivity and plasticity.