Tal Linzen - Assistant Professor at New York University

Tal Linzen

Assistant Professor at New York University

New York, New York, United States

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Summary

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Tal Linzen is an Assistant Professor and researcher with 16 years of experience at the intersection of computational linguistics, cognitive science, and software engineering. Based in New York, he builds and evaluates probabilistic models of language comprehension and acquisition, combining computational modeling with behavioral and neural experiments. His work spans academia—from postdoctoral research at École normale supérieure to faculty roles at Johns Hopkins and NYU—and practical software development, including early engineering roles at IBM and contributions to production systems. He brings a rare blend of rigorous empirical methods and hands-on coding, exemplified by technical-writing contributions that improved documentation for the widely used MNE‑Python neuroimaging library. Tal teaches advanced quantitative methods and has a strong foundation in mathematics and linguistics (BSc, MA, PhD), enabling him to translate theoretical questions into reproducible computational pipelines. Colleagues value his clarity in explaining complex models and his knack for making research software more accessible to interdisciplinary users.

16 years of coding experience

11 years of employment as a software developer

Bachelor of Science (B.Sc.), Mathematics and Linguistics, Bachelor of Science (B.Sc.), Mathematics and Linguistics at Tel Aviv University

PhD, Linguistics, PhD, Linguistics at NYU

MLSS

English, Hebrew, Spanish

Stackoverflow

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Github Skills (7)

python10

neuroimaging10

documentation10

el9

ceph9

ec9

Programming languages (3)

HTMLJupyter NotebookPython

Github contributions (5)

mne-tools/mne-python

Nov 2013 - Feb 2014

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

Role in this project:

Technical Writer

Contributions:44 commits, 3 comments, 1 issue in 3 months

Contributions summary:Tal's contributions primarily focused on improving the documentation within the MNE-python repository. Their commits involved refining docstrings, adding code examples with the correct formatting, and clarifying procedures, especially regarding downsampled data and the use of trial IDs. These changes aimed to provide more clarity and guidance for users, enhancing the usability of the MNE-python library. The user also expanded the docstring of drop_log and refined other documentation throughout the code.

visualizationneuroimagingneurosciencepythonstatistics

TalLinzen/tallinzen.github.io

Sep 2021 - Apr 2025

Contributions:122 pushes, 1 branch in 3 years 7 months

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