Ángel Muñoz González

Internet of Brains: Removing body constraints, integrating the senses

The Internet of the Brains (IoB) project aims to free humans from their physical or brain limitations. In the multisense foundations project we aim to develop a platform to bring this future earlier by connecting brain, internet and robotics via brain-machine interfaces, but also by acquiring other physiological data. Such platform could help researchers and creators to develop personalize and integrated solutions faster than with the currently limited solutions. In Araya Inc, I work as a Chief Researcher leading the technical criteria, design and development of such platform.

Early detection of Alzheimer with neuroimaging AI biomarkers

Research and innovation for Braineer and other products. Researching on the early detection of Alzheimer disease based on the concept of quantifying brain volume from brain MRI data and using technology to convert the tacit knowledge of medical specialists into explicit knowledge. In Splink Inc, I researched on Artificial Intelligence algorithms and proposed biomarkers based on image analysis for medical software platforms.

Brain signals, emotional responses and new entertainment paths

Electroencephalogram brain signals can be used for a variety of purposes, among these, one particular area of interest is the recognition of emotional states. During my PhD research I had the chance to dive deep into the opportunities and challenges of brain information. In this particular project, the focus evolved around the emotional response to music stimuli, and how such information could be used to offer new solutions in entertainment in combination with Virtual Reality.

Building athematical models for immunological cell populations

Neutrophils are a kind of white cells that are part of the human immune system. These cells have a relatively short lifespan, during which we can find them across different organ tissues. By using advanced mathematical models based on Partial Differential Equations and in Bayesian statistics we can estimate these lifespans in each different organ. Thanks to a collaboration with multiple research teams, I could work on such hypothesis. Such kind of knowledge can later be used, for example, for enhanced pharmaceutical products or more reliable treatments.

Automating the chest diseases diagnosis by using X-rays

Chest X-rays are highly useful for the diagnosis of a big variety of diseases. Thanks to Machine Learning, relying on automated models for pathology detection in chest radiographs is possible now. In this project, I worked developing different Deep Learning networks based on Convolutional Neural Networks (CNN) and on Residual Neural Networks (RNN), comparing them with rigor around validation and bias checks.

Health status risk-based alarm systems in wearables

Wearables are a big source of physiological data and are highly useful for tracking the health condition of the general population. However, they normally offer the feedback for different metrics without taking into consideration the inter-connection between those data. In this project, I worked integrating multiple hardware into a software to create an Early Warning Score system that considers such relations between different health metrics, creating a health-check system more adequate for clinical pipelines.