Dr. Manuel Graña, Universidad del País Vasco (Spain)

Dr. Javier de Lope, Universidad Politécnica de Madrid (Spain)


Cyberphysical systems have emerged as a global paradigm for the development of technological solutions to the most diverse problems, stemming from the Internet of Things (IoT) pervasiveness and ubiquity. The myriad of cyberphysical systems allow to measure and control all kind of systems in close contact with the human users.

Therefore, machine learning can effectively provide relevant information to take great strides toward understanding how the brain works. The main goal of the workshop is to build a bridge between two scientific communities, the machine learning community, including lead scientists in deep learning and related areas within pattern recognition and artificial intelligence, and the neuroscience community.

As diverse as the cyberphysical devices and their roles in the systems, are the computational tools developed and used to control them and to extract information from them, ranging from embedded system programming needed for their deployment to the spatial-temporal analysis of the data of sensor networks, or the increasingly sophisticated dialog systems of social robotics as an instance of social cyberphysical systems.

Prominent are the techniques devoted to the observation of human activities and analysis of the sensor information towards modeling human behavior. On the other hand, Computational Neurethology is directed to the understanding and modeling of the correlation between externally observable and measurable behavior (human or animal) and the internal neuronal activity as measured by brain activity observation cyberphysical systems. The aim is to obtain a high resolution map between neural activity and behavior. Such map will be valuable to measure the actual impact of treatments in many psychological and psychiatric conditions.

As examples of synergistic applications arising from the interplay of cyberphysical systems we mention two. The first is the evaluation of the introduction of novel cyberphysical aids for children and people with special educational needs. For instance, there are many proposals relative to the use of robotics in the educational setting, whose careful evaluation would benefit from the innovative use of Computational Neuroethology methods and techniques. The second is the evaluation of treatments of elder people suffering from conditions such as frailty or dementia. The workshop is supported by project CybSPEED funded by the MSCA-RISE call with grant 777720, and FEDER funded MINECO TIN2017-85827-P.

The session invites papers from all perspectives of the target interplay:

  • Design of cyberphysical systems for Computational Neuroethology.
  • Design of cyberphysical systems for neurological related.
  • Computational approaches such as machine learning, signal processing, deep learning, etc.
  • Proposal of experimental datasets and their publication.
  • Case studies including the presentation of ongoing experimentation.
  • Legal and ethical issues.