Education
- B.S. in GitHub, GitHub University, 2012
- M.S. in Jekyll, GitHub University, 2014
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
Work experience
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Book Chapter: Deep learning methods for EEG neural classification
Nakagome S, Craik A, Ravindran AS, He Y, Cruz‐Garza JG, and Contreras‐Vidal JL. Springer Handbook of Neuroengineering. In: ed. by Thakor NV. Springer Nature. Chap. Deep learning methods for EEG neural classification. In Press
A Wrist Worn SpO2 Monitor with Custom Finger Probe for Motion Artifact Removal
Preejith, S. P., Ravindran, A. S., Hajare, R., Joseph, J., & Sivaprakasam, M. (2016, August). A wrist worn SpO 2 monitor with custom finger probe for motion artifact removal. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 5777-5780). IEEE.
Assaying neural activity of children during video game play in public spaces: a deep learning approach
Ravindran, A. S., Mobiny, A., Cruz-Garza, J. G., Paek, A., Kopteva, A., & Vidal, J. L. C. (2019). Assaying neural activity of children during video game play in public spaces: a deep learning approach. Journal of neural engineering, 16(3), 036028.
Emotion Recognition by Point Process Characterization of Heartbeat Dynamics
Ravindran, A. S., Nakagome, S., Wickramasuriya, D. S., Contreras-Vidal, J. L., & Faghih, R. T. (2019, November). Emotion recognition by point process characterization of heartbeat dynamics. In 2019 IEEE Healthcare Innovations and Point of Care Technologies,(HI-POCT) (pp. 13-16). IEEE.
An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding
Nakagome, S., Luu, T. P., He, Y., Ravindran, A. S., & Contreras-Vidal, J. L. (2020). An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding. Scientific reports, 10(1), 1-17.
Interpretable Deep Learning Models for Single Trial Prediction of Balance Loss
Ravindran, A. S., Cestari, M., Malaya, C., John, I., Francisco, G. E., Layne, C., & Vidal, J. L. C. (2020, October). Interpretable Deep Learning Models for Single Trial Prediction of Balance Loss. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 268-273). IEEE.
Characterization of the Stages of Creative Writing With Mobile EEG Using Generalized Partial Directed Coherence
Cruz-Garza, J. G., Sujatha Ravindran, A., Kopteva, A. E., Rivera Garza, C., & Contreras-Vidal, J. L. (2020). Characterization of the Stages of Creative Writing With Mobile EEG Using Generalized Partial Directed Coherence. Frontiers in human neuroscience, 14, 533.
A Roadmap towards Standards for Neurally Controlled End Effectors
Paek, A. Y., Brantley, J. A., Ravindran, A. S., Nathan, K., He, Y., Eguren, D., ... & Contreras-Vidal, J. L. (2021). A Roadmap towards Standards for Neurally Controlled End Effectors. IEEE open journal of engineering in medicine and biology, 2.
Talks
Tutorial: Introductory Workshop to EEG Pre-processing
Workshop at Zoom | BRAIN Center, Houston
Tutorial: Explainable Deep Learning Models to Study EEG
Workshop at Zoom, BRAIN Center, Houston
Neura Pod Podcast: Neuralink Pros and Cons w/ Akshay Ravindran
Talk at Zoom, Houston
Nahual Project GAN Pilot Version Demonstration @ the Moody Center for the Arts
Demonstration at Moody Center for the Arts, Rice University
Panel Discussion- Things You Wish You Knew When You Started Your Ph.D.
Talk at Zoom, Houston
Nahual Project 2nd Demonstration @ Theatre, UH Student Center
Demonstration at Theatre, Student Center, UH
Teaching
Service and leadership
- Currently signed in to 43 different slack teams