Saying the winners of the 2021 Engineering Approaches to Accountable Neural Interface Design request for proposals
In May 2021, Facebook launched the “Engineering Approaches to Responsible Neural Interface Design” (RFP) tender. Today we announce the winners of this award.
VIEW RFPFacebook Reality Labs (FRL) researches neural interfaces as potential input paradigms for the control of augmented reality and / or virtual reality systems. In line with Facebook’s principles of responsible innovation, FRL neurotechnology researchers are dedicated to uncovering and addressing neuroethical considerations associated with system design. As part of this effort, FRL has solicited proposals that use technology to incorporate the following principles of responsible innovation: keeping everyone in mind by promoting inclusivity in system design, putting people first by carefully handling data, and providing critical controls by developing tools and methods for data management and data protection.
With the awards presented as part of this call, Facebook neurotechnology researchers aim to deepen their relationships with the academic community and advocate innovative ideas that promote the ethical development of neurotechnology. The areas of interest of this call for proposals focused on the following topics:
- Including optical neurotechnology
- Including surface electromyography (EMG) technology
- Data protection methods for handling neural and neuromuscular data
The team has reviewed 50 high quality suggestions and is happy to announce the six winning suggestions below. Thank you to everyone who took the time to submit a proposal and congratulations to the winners.
Research Award Winner
The influence of hair type and skin pigmentation on the fNIRS signal quality
Meryem Ayse Yucel, Bernhard Zimmermann, David Boas, Parya Farzam (University of Boston)
Framework for diverse EMG gesture recognition
Jennifer Mankoff, Momona Yamagami (University of Washington)
Privacy-preserving federated learning for minimized fNIRS data
Xiali Hei (University of Louisiana at Lafayette)
Data protection through federated learning with Gaussian processes
Ethan Fetaya, Gal Chechik, Jose Zariffa (Bar Ilan University)
Racially Integrative Optical Technology: Develop fNIRS for dark skin and curly hair
Sossena Wood, Jana Kainerstorfer, Pulkit Grover (Carnegie Mellon University)
User-guided EMG data acquisition that covers all physical abilities
Jacob A. George (University of Utah)