# /research
Where neuroscience
meets security.
My research at Aether explores brain–computer interfaces with a security-first lens: encrypting neural data, hardening the BCI pipeline, and building resilient systems for human–machine interaction.
thesis
Brain–computer interfaces are moving from labs to real applications — prosthetics, assistive tech, biomedical devices. The data they generate is uniquely personal, irreplaceable, and irrevocable. Securing the BCI stack is not an afterthought; it's a precondition for this technology to exist at scale.
focus areas
Threat modeling for brain–computer interfaces, identifying attack surfaces across acquisition, transmission, processing, and inference stages.
Approaches to protecting neural signals — at rest and in motion — without compromising the real-time constraints of BCI systems.
Designing BCI architectures that fail safe, isolate compromise, and remain operational under adversarial conditions.
Processing pipelines for prosthetic control and human–machine interaction — the substrate everything else builds on.
Bridging neuroscience and AI for real-world applications in biomedical engineering and assistive technologies.
roles at aether
AI Engineer, Systems Engineer, and Hardware Engineer specializing in advanced AI-driven systems, hardware integration, and BCI technologies.
Conducting advanced research in AI, neurotechnology, and brain–computer interfaces — focused on neural signal processing, prosthetic control, and human–machine interaction.
methods
- Neural signal processing — preprocessing, feature extraction, classification
- Experimental design — hypothesis-driven, controlled, reproducible
- Uncertainty modeling — confidence intervals, error bounds, validation
- Reproducibility — version-controlled experiments, peer review, open methods
- Algorithm development — from neural-signal processing to security primitives
- Lab-to-field translation — bringing research from simulation to physical systems