Paolo Gabriel, PhD

My PhD research of neural correlates to naturalistic human behaviors was actually a study in practical signal processing of noisy time-series data. These data were noisy because a) recording in hospital environments offer many challenges; b) biological signals are noisy; and c) natural behaviors vary from day to day. I spent equal amounts of time figuring out how to record hospital videos, how to annotate days of recordings using computer vision, and how to use brain activity to decode natural human movements. Consequently, I developed a deep appreciation for the potential ways computer vision can augment patient care in the hospital, especially with semi-supervised and continuous monitoring.

I graduated from Stanford with a BS in Engineering Physics in 2013 and went on to complete a PhD in Electrical Engineering at the University of California, San Diego. After completing my degree in Fall 2019, I was excited to continue the spirit of my work at LookDeep Health. I believe my experiences in computer vision processing, time-series data analysis, and clinical monitoring strongly align with this company, and I want to help make our shared dream come true.

Outside of LookDeep, I find myself fusing my skills with my passions — organizing long and complicated cooks to fulfill my big meal dreams, applying my programming skills to support digital art, volunteering my time and energy to help other makers build things.