Zander Labs

Neuroadaptivity for Autonomous Systems (NAFAS)

Neuroadaptivity for Autonomous Systems (NAFAS) is an endeavor funded by the German federal agency Agentur für Innovation in der Cybersicherheit - “Innovation for Cybersecurity" (Cyber Agency) that seeks to revolutionize human-computer interaction and artificial intelligence through neuroadaptive technology.


The project’s main goal is to develop neurotechnological prototypes to simplify communication between humans and partially autonomous systems. And enable artificial intelligence to directly learn from the human brain to adopt skills and understand human values.

About NAFAS

Despite significant advancements in technology, machines continue to lag behind humans in understanding, learning from, and responding to human emotions, mental states, and cognitive decision-making processes. This limitation has resulted in cumbersome communication between humans and technology, constraining the potential of human-computer interaction.


Neural human-computer interaction without invasive interventions


Zander Labs will develop a neurotechnological prototype capable of extracting information from the brain, allowing a person to exchange information with an external system using only their brain. This brain-based information exchange can, for example, be used to instruct a computer to perform a task, or to teach an artificial intelligence new skills.


Through neuroadaptive human-computer interaction and neuroadaptive artificial intelligence, Zander Labs’ researchers will go beyond traditional human-computer interaction techniques to facilitate the development of a deeply personalized technological user experience, enhancing the efficiency of autonomous systems.


NAFAS will leverage naturally-occurring brain activity data, decoded using passive brain-computer interfaces, to create adaptive systems capable of learning from the cognitive and affective processes of humans. 


During the research process, both hard- and software will be developed to allow brain activity to be safely and effectively decoded. Based on this, the activity will be translated into categories and transferred to artificial systems, enabling these to interpret human mental states in any given context.


The goal is to explore a new generation of machines that can adapt in real-time to the cognitive and affective states of the user, personalizing the user experience and improving the effectiveness of autonomous systems without requiring manual input.


Background

On October 7, 2022, the German federal agency Agentur für Innovation in der Cybersicherheit - “Innovation for Cybersecurity" published its tender procedure "Secure Neural Human-Machine Interaction" to  ensure the secure and societally beneficial early-stage development of this technology within the Federal Republic of Germany.


After evaluating four other competitors, the Cyber Agency awarded Zander Labs’ with a 30-million-euro contract for its four-year project proposal providing the most innovative research idea. This is the largest individual funding for a research project in the European Union.


Research team


The NAFAS project will be led by Professor Dr. Thorsten O. Zander, a pioneer in the field of passive brain-computer interfaces and neuroadaptive technology—who also serves as Zander Labs CTO—and Gerard de Jager, Zander Labs’ CEO and chairman of the NAFAS Steering Board.



As the project progresses, the team will expand and new hiring processes will take place to fulfil different research positions.

 


  • Professor Dr. Thorsten O. Zander - Scientific Project Director
  • Mr. Gerard De Jager - Operations Project Director
  • Dr. Laurens R. Krol - Scientific Project Coordinator
  • Mr. Jonathan Zwaan - Operations Project Coordinator
  • Dr. Johanna Wagner - Team Leader
  • Dr. Alin Chitu - Team Leader
  • Dr. Teodoro Solis Escalante - Team Leader

Partners

The following partners will take part in the NAFAS project, developing software and/or hardware solutions:

More information

Questions? Please contact us: info@zanderlabs.com

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