Data analysis for health 

Experience analyzing data for health and research purposes. Detection and processing of signals from wearable sensors and mobile phones for diagnosis or monitoring of disease, including cardiac diseases, sleep apnea, spinal cord injury and others. Treating Nuclear Magnetic resonance and Hyperpolarized nuclear magnetic resonance data for imaging and spectroscopy (eg, in vitro cell metabolic studies or in vivo mouse imaging). Advanced algorithms and machine learning for data processing for biomarker discovery, image analysis, chromatography and spectrometry data.

  • Non-invasive biomedical data obtention, processing and analysis from wearables and mobile phones for disease diagnosis, monitoring and screening. Experience on Obtrusive breathing disorders (OSA, COPD, COVID-19), Cardiac disorders (Brugada syndrome, Ischemia), Neuromechanical diseases (Neurorehabilitation, SCI), and gastrointestinal diseases.
  • Transcriptomic and metabolic profiling for prediction of implantation success of embryos in humans.
  • Develop algorithmic solutions for the automatic processing of Gas Sensor Array, Gas Chromatography – Ion Mobility Spectrometry (IMS), Nuclear Magnetic Resonance, and Mass Spectrometry (GC/LC-MS, MSI) data.
  • Development of data processing methods (including machine learning tools) to resolve molecular heterogeneity in mass spectrometry images, validated on colorectal cancer tissues.