Medical Physics, AI and Neurotechnology · University of Rome Tor Vergata

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FISMED / PEOPLE

Grigorii Rashkov

Doctoral Researcher · University of Rome Tor Vergata

BACKGROUND

Biography

Grigorii Rashkov studies the relationship between neural activity and semantic representations, using machine learning to analyse and decode brain signals. His research includes the alignment of EEG, MEG and functional MRI representations for visual decoding. He holds a master's degree in Applied Mathematics and Physics from the Moscow Institute of Physics and Technology. His previous research experience includes the Institute of Higher Nervous Activity and Neurophysiology and the Artificial Intelligence Research Institute in Moscow.

RESEARCH & EXPERTISE

Research interests

  • Brain decoding
  • Semantic representations
  • Multimodal neuroimaging
  • Deep learning

RESEARCH OUTPUT

Selected publications

  1. Towards neural foundation models for vision: Aligning EEG, MEG, and fMRI representations for decoding, encoding, and modality conversionInformation Fusion · 2026
    This paper presents a novel approach towards creating a foundational model for aligning neural data and visual stimuli across multimodal representationsof brain activity by leveraging contrastive learning. We used electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) data. Our framework's capabilities are demonstrated through three key experiments: decoding visual information from neural data, encoding images into neural representations, and converting between neural modalities. The results highlight the model's ability to accurately capture semantic information across different brain imaging techniques, illustrating its potential in decoding, encoding, and modality conversion tasks.

LABORATORIES & RESEARCH

Related research

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