Nathaniel See

Nathaniel See has a diverse work experience in various research and scientific roles. Nathaniel is currently working as a Lead Machine Learning Research Scientist at Omneky since January 2023. Prior to this, they worked at Meta as an Applied Research Scientist (Machine Learning) from December 2021 to January 2023.

From January 2019 to December 2021, Nathaniel worked at Applied Materials as a Data Scientist. Here, they developed innovative techniques to enhance the performance of deep neural networks on experimental analog computation hardware. Nathaniel also utilized self-supervised and semi-supervised deep learning and computer vision techniques to detect defects in semiconductor production. Additionally, Nathaniel built deep reinforcement learning models to automate and optimize warehouse processes.

Before joining Applied Materials, Nathaniel served as a Graduate Research Assistant at UC Irvine from September 2016 to September 2017. In this role, their responsibilities involved setting up experiments to measure structures in two-dimensional foams and implementing MATLAB code to identify bubble clusters in image data.

Prior to their role at UC Irvine, Nathaniel worked as a Graduate Teaching Assistant at UC Irvine from an unspecified period in 2014 to 2016.

Furthermore, Nathaniel gained experience as an Undergraduate Research Assistant at California State University-Los Angeles from an unspecified period in 2012 to 2014. Nathaniel'swork involved setting up Monte-Carlo simulation runs for comparison with scattering experiments at Jefferson Lab and creating histograms using CERN's ROOT C++ library based on simulation results.

Nathaniel See completed their Bachelor of Science in Physics at California State University-Los Angeles from 2010 to 2014. Following their undergraduate studies, they pursued a Master of Science in Physics at UC Irvine from 2014 to 2017.