Please join Project Jupyter in welcoming Mike Pacer to the core development 
team!


Mike Pacer is a post-doctoral scholar with Fernando Perez at the Berkeley 
Institute for Data Science (BIDS). He earned his PhD at UC Berkeley in 
Psychology after undergraduate training in Psychology at Yale University. 
Mike’s 
graduate research focused on building computational and experimental 
accounts of causal induction and explanation, particularly comparing 
computational models’ responses to human responses when all are given the 
same data. This required building a mathematical framework for 
continuous-time causal theories (which are generative models for 
continuous-time causal Bayesian networks), as well as constructing engines 
for programmatically manipulating, generating, and querying probabilistic 
graphical models (e.g., [cbnx](
https://github.com/michaelpacer/Causal-Bayesian-NetworkX) and 
[hidden-structure-inference](
https://github.com/michaelpacer/hidden_structure_inference)). Mike is one 
of the founders of Amperser Labs, which developed Proselint (a linter for 
prose).


Mike will be working on integrating Jupyter (particularly, Jupyter 
notebooks) with the scientific publication pipeline. When not working on 
machine learning, cognitive science, automated advice giving and Jupyter, 
Mike studies the history of science and medicine, studies the history of 
coded communication (paper, pens, ink, mathematical notation, writing 
systems, typography, audio recording, telegraphs &c.), draws, and thinks 
about how to computationally model (basically) everything.


Welcome Mike!


-

Jamie Whitacre

Jupyter Technical Project Manager

Berkeley Institute for Data Science (BIDS)

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