I'm a cognitive neuroscientist and data scientist passionate about neuroimaging, signal processing, and data science. My work spans both academia and industry, where I apply advanced data science and AI techniques to solve complex problems in neuroscience and healthcare.

• Naturalistic Neuroimaging Database (version 2) 🧠
  A large-scale open-access neuroimaging dataset featuring eye-tracking, tonotopy, retinotopy, somatotopy, and cognitive assessments. Open neuroimaging datasets drive scientific transparency, reproducibility, and innovation by allowing researchers worldwide to validate findings, develop new analytical techniques, and apply machine learning models to better understand the brain. Unlike traditional controlled experiments, naturalistic paradigms provide richer, more ecologically valid insights into cognition and behavior.

• Movement Reduction System for Improved MRI Data 🧠
  Developing and validating a head movement reduction system for MRI experiments. This project involves fMRI preprocessing, statistical modeling, and signal processing to assess the system’s effectiveness in improving data quality. We compare the quality of fMRI data with and without the system to quantify its impact on motion artifacts and overall signal integrity.

• Neurometry 🏥
  A data-driven approach to cognitive neuroscience, leveraging machine learning for neuropsychiatric monitoring. At Neurometry, we focus on real-world AI applications in neurotech, including clinical decision support and cognitive well-being analysis.

• Google Scholar: My Google Scholar
• Twitter/X: @egorlevchenko_
• Bluesky: @egorlevchenko.bsky.social