Contact
email: sdgh.ebrahimi@gmail.com
phone: 650-766-3687
Resume
I am interested in applying machine learning and quantitative analysis to solve engineering and scientific problems. During my PhD at stanford I used these techniques to understand information coding and communication in the mamalian brain the result of which was published in the Nature magazine. In addition to data science and machine learning , I am a profiecient software developer with a deep understanding of computer hardware.
Applied statistical analysis and machine learning methods on large scale neural activity recordings of mouse cortex to study communication between brain areas and stability of neural decoders over time. The results were published in the Nature journal
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Designed an embedded AI and developed the firmware for a wearable device to decode a patient’s hand movement intentions using AI and activate intended hand and finger movements using neuromuscular stimulation. Lead the software development for the wireless wearable smart stimulator that is controlled by a mobile app and drives wearable Neuro-Moscular Interfaces.
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Designed and assembled a compact brain imaging Virtual Reality (VR) environment for mice. Collected and analyzed the brain activity during a VR navigation through natural scenes while tracking the animal’s pupil movements using Deeplabcut. Using deep encoder-decoder networks, reconstructed the images that the mouse was looking at from its neural activity in the visual cortex. Conceived and led the project during post-doc and was awarded a Simons Foundation grant. A paper containing our initial results is under review for NeuroIPS 2022.
Designed a real-time clustering method to summarize large numbers of failure events on computer networks. The outcome of this project was patented by Oracle.
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Journal and Conference Papers
1. Ebrahimi, S., Lecoq, J., Rumyantsev, O., Tasci, T., Zhang, Y., Irimia, C., Li, J., Ganguli, S. and Schnitzer, M.J. (2022). Emergent reliability in sensory cortical coding and inter-area communication. Nature 605, 713–721.
2. Jiang, Y., Akengin, H.O., Zhou, J., Aslihak, M.A., Li, Y., Chrapkiewicz, R., Hernandez, O., Ebrahimi, S., et al. (2024). ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets. Advances in Neural Information Processing Systems (NeurIPS) 37, 79095–79143.
3. Chandrasekaran, S., Bhagat, N.A., Ramdeo, R., Ebrahimi, S., Sharma, P.D., Griffin, D.G., Stein, A., Harkema, S.J. and Bouton, C.E. (2023). Targeted transcutaneous spinal cord stimulation promotes persistent recovery of upper limb strength and tactile sensation in spinal cord injury: a pilot study. Frontiers in Neuroscience 17, 1210328.
4. Chandrasekaran, S., Bhagat, N.A., Ramdeo, R., Ebrahimi, S., Sharma, P.D., Griffin, D.G., Stein, A., Harkema, S.J. and Bouton, C.E. (2023). Case study: persistent recovery of hand movement and tactile sensation in peripheral nerve injury using targeted transcutaneous spinal cord stimulation. Frontiers in Neuroscience 17, 1210544.
5. Ebrahimi, M.S. and Abadi, H.K. (2021). Study of residual networks for image recognition. In Intelligent Computing: Proceedings of the 2021 Computing Conference (pp. 754–763). Springer.
6. Ebrahimi, M.S., Hills, G., Sabry, M.M., Shulaker, M.M., Wei, H., Wu, T.F., Mitra, S. and Wong, H.S.P. (2014). Monolithic 3D integration advances and challenges: From technology to system levels. In IEEE S3S Conference (pp. 1–2).
7. Ebrahimi, M.S., Daraei, M.H., Behzadan, V., Khajooeizadeh, A., Behrostaghi, S.A. and Tajvidi, M. (2011). A novel utilization of cluster-tree wireless sensor networks for situation awareness in smart grids. In IEEE PES Innovative Smart Grid Technologies (pp. 1–5).
Preprints
8. Dinc, F., Blanco-Pozo, M., Klindt, D., Acosta, F., Sylber, C., Jiang, Y., Ebrahimi, S., Shai, A., Tanaka, H., Yuan, P., Miolane, N. and Schnitzer, M.J. (2026). A geometric and dynamical theory of latent computations in biological neural networks. bioRxiv (under review at Nature Neuroscience).
9. Chetty, N., Kacker, K., Feldman, A.K., Yoo, P.E., Bennett, J., Fry, A., Tal, I., Hardy, N.F., Ebrahimi, S., et al. (2025). Signal properties and stability of a chronically implanted endovascular brain computer interface. medRxiv.
10. Dinc, F., Blanco-Pozo, M., Klindt, D., Acosta, F., Jiang, Y., Ebrahimi, S., Shai, A., Tanaka, H., Yuan, P., Schnitzer, M.J. and Miolane, N. (2025). Latent computing by biological neural networks: A dynamical systems framework. arXiv:2502.14337.
11. Chandrasekaran, S., Bhagat, N.A., Ramdeo, R., Ebrahimi, S., Sharma, P.D., Stein, A., Griffin, D.G., Harkema, S.J. and Bouton, C.E. (2022). Targeted transcutaneous cervical spinal cord stimulation promotes upper limb recovery in spinal cord and peripheral nerve injury. medRxiv.
Patents
12. Hardy, N.F., Echavarria, C., Herbers, C., Ebrahimi, S., Bennett, J. and Yoo, P.E. (2025). Systems for controlling one or more devices using a signal control unit. U.S. Patent 12,461,596.
13. Hardy, N.F., Echavarria, C., Herbers, C., Ebrahimi, S., Bennett, J. and Yoo, P.E. (2026). Systems for controlling one or more devices using a signal control unit. U.S. Patent Application 19/341,581.
14. Bouton, C., Ebrahimi, S., Toro, J., Leavitt, J. and Niewiadomski, J. (2025). Addressable serial electrode arrays for neurostimulation and/or recording applications and wearable patch system with on-board motion sensing and magnetically attached disposable for rehabilitation and physical therapy applications. U.S. Patent Application 18/854,837.
15. Ebrahimi, M.S., Patti, R.H.R. and Garvey, D. (2020). Using and updating topological relationships amongst a set of nodes in event clustering. U.S. Patent 10,678,610 (Oracle).
Full and up-to-date list on Google Scholar.
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