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AgneGris/README.md

Hi, I'm Agnese 👋

I'm a Research Associate at the Imperial–Meta Wearable Neural Interfaces Research Centre, Imperial College London. I develop machine-learning and signal-processing methods to extract individual motor neuron activity from high-density electromyography (EMG). I apply this work to neural interfaces and assistive technology, including research after spinal cord injury.

🌐 Website: agnegris.github.io

Open-source tools

  • Swarm Contrastive Decomposition: a Python/PyTorch package that decomposes high-density EMG using particle-swarm-optimised source separation.
  • SCD Studio: a Qt/Python desktop app for GPU-accelerated decomposition and motor unit review and editing.
  • MUniverse: a simulation and benchmarking suite for motor unit decomposition (NeurIPS 2025, Datasets & Benchmarks Track; co-author).

Find me

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  1. swarm-contrastive-decomposition swarm-contrastive-decomposition Public

    Decomposition of Neurophysiological Time Series Signals with a Particle Swarm Optimised Independence Estimator

    Python 29 11

  2. scd-studio scd-studio Public

    Desktop tool for GPU-accelerated decomposition, review, and editing of high-density EMG recordings.

    Python 8 6