Carlos Johnson-Cruz

Carlos Johnson-Cruz, PhD, is a Postdoctoral Research Scientist at the University of California, San Francisco, where expertise includes building and optimizing Python data extraction pipelines and deep learning models for neural time-series data analysis. As a Neuroscience Doctoral Candidate, Carlos developed machine learning neural decoding models that achieved an average accuracy of 90% while leading multi-year studies on neural encoding. Prior experience includes a Data Analysis Internship at Evidation, analyzing wearable sensor data, and recognition as a DS4A Distinguished Scholar for impactful COVID-19 research. Carlos's academic background features a PhD in Neuroscience from UCSF and a Bachelor's Degree with Honors in Neuroscience from Amherst College.