Hi! My name is Patrick Beukema. I am scientist and engineer passionate about applying machine learning and artificial intelligence to global environmental and healthcare challenges. Currently I work on machine learning and AI at DocuSign. Previously, I worked at a neurotechnology/AI startup where I built models for neural decoding and computer vision. I am also interested in improving scientific reproducibility by teaching foundational coding and data science skills to academic researchers.
I hold a Ph.D in neuroscience from the Center for Neuroscience at the University of Pittsburgh and the Center for the Neural Basis of Cognition at Carnegie Mellon University. My research focused on neural population patterns and how they change during learning. Before that, I studied recurrent networks and causal inference at Carnegie Mellon University (M.S. Logic). And before that, I spent several great years at McGill, did some research on biodiversity, and learned a few of the subtleties around mixing Montreal winters and brakeless fixed gear bikes.
|Oct 6, 2020||Talk: “A Unified CV, OCR, & NLP Model Pipeline for Document Understanding”|
|Dec 16, 2018||“Modernizing Academic Data Science” article|
|Nov 18, 2018||Raw data from plasticity research now on OpenNeuro [dataset1, dataset2].|
|Aug 24, 2018||Workshop on reproducible data science, NeuroHackademy workshop materials.|
|Apr 20, 2018||“Stability of Neural Representational Geometries” Ph.D dissertation.|
|Jan 29, 2018||“Plasticity of neuronal representations” on bioRxiv [data] [ipynb] [manuscript]|
|Jan 17, 2018||“Parallel motor learning networks”, Cosyne 2018.|
|Nov 15, 2017||“Algorithms supporting skill consolidation” Current Opinion|
|Oct 30, 2017||Talk “Statistical Abuse in Biomedical Research” [slides]|