Geeling Chau is a PhD student and research engineer at Caltech with a decade of hands-on experience at the intersection of machine learning, neural engineering, and biosensing. She develops adversarial models and large-scale data pipelines to improve brain–machine interface decodability and has worked with fUS, EEG/sEEG, and single-neuron datasets across multiple labs. Her background in computer engineering and cognitive science, plus three Microsoft software internships, lets her bridge production-grade software and experimental neuroscience workflows. Geeling combines technical depth in signal processing and ML with leadership and teamwork skills cultivated in interdisciplinary research teams. An under-the-radar strength is her focus on practical tooling for terabyte-scale neural data quality and reproducible BMI decoding.
10 years of coding experience
2 years of employment as a software developer
University of California San Diego
High School Diploma, High School Diploma at Stanford Online High School
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