Yahia Ali is a software engineer and neurotech researcher with ~8 years of experience building real-time ML-enabled systems for brain-computer interfaces and clinical research. He developed a sub-millisecond BCI software framework adopted by multiple leading clinical trials and engineered calibration-free deep learning pipelines for neural signal stabilization, demonstrating feasibility on non-human primate datasets. His work spans end-to-end infrastructure and embedded systems—managing GPU farms and converting robotic control to low-cost embedded solutions—ensuring high uptime for critical experiments. Based in San Francisco and finishing a PhD in Biomedical Engineering, he blends rigorous academic research with production-grade software delivery and seeks machine learning/software roles starting Fall 2025. An under-the-radar strength is his track record of translating lab prototypes into clinical-ready tools that replace legacy platforms while enabling modern ML workflows.
Backend for Real-time Asynchronous Neural Decoding (BRAND)
Contributions:1 PR, 11 pushes, 3 branches in 1 year 9 months
asynchronousbackend
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