Block-Based Brain Computer Interface Software
EEG BCI Software

Quickly develop neurofeedback applications with a block-based programming environment

Facilitating Human-Robot Interaction Evaluation with Neurophysiological Visualizations
Brain-Robot Interface

Exploring links between users’ cognitive state and spatial information from robots

BCI.js - An Electroencephalography Toolkit Built on Modern Web Technologies

JavaScript based EEG signal processing for BCI applications

Artistic BCI
Artistic BCI

NeuroBrush - a web-based EEG application that allows users to paint abstract art competitively

Brain-Drone Race
Brain-Drone Race

Competitors had to out-focus opponents in a drone race influenced by electrical signals emitted from the brain

Autism Spectrum Disorder EEG Research

Investigating ways to provide rich automated feedback that assists parents with learning vital techniques for joint attention and social communication


Chris Crawford headshot

Chris Crawford


Nick headshot


PhD Student

Amanda headshot


PhD Student

Bryan headshot


PhD Student

Jenna headshot


MS Student

Pierce headshot


Undergraduate Student

Ajay headshot


Undergraduate Student

Will headshot


Undergraduate Student

Shomari headshot


Undergraduate Student


Stegman, P., Crawford, C.S., and Gray, J., (2018). WebBCI: An Electroencephalography Toolkit Built on Modern Web Technologies. HCI International 2018, July 15-20, 2018, Las Vegas, NV, USA. Status: Accepted

Cioli, N., Holloman, A., and Crawford, C., (2018). NeuroBrush: An Artistic Multi-Modal, Interactive Painting Competition. CHI 18' Artistic BCI Workshop, April 22, 2018, Montreal, QC, Canada. Status: Accepted

Crawford, C.S., Andujar, M., and Gilbert, J.E., (2018). Brain Computer Interface for Novice Programmers. ACM SIGCSE Technical Symposium on Computer Science Education, February 21-24, 2018, Baltimore, MA, USA, pp. 32 -37.

Crawford, C.S., Andujar, M., and Gilbert, J.E., (2017). Neurophysiological Heat Maps for Human-Robot Interaction Evaluation. In Proceedings of 2017 AAAI Fall Symposium Series: Artificial Intelligence for Human-Robot Interaction AAAI Technical Report FS-17-01, November 9-11, 2017, Arlington, VA, USA, pp. 90-93.

Lieblein, R., Hunter, C., Garcia, S., Andujar, M., Crawford, C. S., & Gilbert, J. E. (2017). NeuroSnap: Expressing the User’s Affective State with Facial Filters. In International Conference on Augmented Cognition (pp. 345-353). Springer, Cham.

Crawford, C.S., Andujar, M., Jackson, F., Applyrs, I., & Gilbert, J.E. (2016). Using a Visual Programing Language to Interact with Visualizations of Electroencephalography Signals. In Proceedings of the 2016 American Society for Engineering Education Southeastern Section (ASEE SE), Tuscaloosa, AL, March 13-15, 2016.

Andujar, M., Crawford, C. S., Nijholt, A., Jackson, F., & Gilbert, J. E. (2015). Artistic brain-computer interfaces: the expression and stimulation of the user’s affective state. Brain-Computer Interfaces, 2(2-3), pp. 60–69.

Crawford, C.S., Badea, C., Bailey, S.W., & Gilbert, J.E. (2015). Using Cr-Y Components to Detect Tongue Protrusion Gestures. In Proceedings of the 33rd Annual ACM CHI 2015 Conference Extended Abstracts, pp. 1331-1336, Seoul, Republic of Korea, April 18-23, 2015.

Crawford, C.S. & Gilbert, J.E. (2015). Towards Analyzing Cooperative Brain-Robot Interfaces Through Affective and Subjective Data. In Proceedings of the 10th Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts pp. 231-232. 2015.

Crawford, C.S., Andujar, M., Jackson, F., Remy, S., & Gilbert, J.E. (2015). User Experience Evaluation Towards Cooperative Brain-Robot Interaction. In Proceedings 17th International Conference Human-Computer Interaction: Design and Evaluation, HCI International 2015, pp. 184–193, Los Angeles, CA, August 2-7, 2015, M. Kurosu (Ed.): Human-Computer Interaction, Part I, Springer LNCS 9169, DOI: 10.1007/978-3-319-20901-2_17.

Crawford, C.S., Andujar M., Remy S., & Gilbert, J.E. (2014). Cloud Infrastructure for Mind-Machine Interface. In Proceedings on the International Conference on Artificial Intelligence (ICAI), pp. 127-133.