Tal Yarkoni
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolTal Yarkoni is a data scientist and informatics engineer with 13 years of experience developing methods and open-source Python tools for behavioral and neuroimaging data management, feature extraction, and statistical analysis. He holds a Ph.D. in Cognitive Neuroscience and has authored over 50 peer-reviewed publications spanning psychology, neuroscience, informatics, and computer science. An active maintainer and contributor to prominent projects like Neurosynth and the Bayesian modeling tools Bambi and PyMC, he brings deep expertise in Bayesian methods and reproducible neuroimaging workflows. Based in the San Francisco Bay Area and currently building at MidJourney, he blends rigorous academic research with production-grade software engineering, often surfacing non-obvious improvements such as automated prior specification and flexible backend support for probabilistic modeling.
13 years of coding experience
Bachelor's degree, Psychology, Bachelor's degree, Psychology at Carleton UniversityPh.D., Cognitive Neuroscience, Ph.D., Cognitive Neuroscience at Washington University in St. Louis
Hebrew, English
Stackoverflow
2,544reputation
116kreached
11answers
2questions
pandas
top-5%
ipython
top-5%
jupyter-notebook
top-1%
python
top-5%
Github Skills (24)
pytest10
python10
pandas10
statistics10
statistic10
pymc10
bayesian10
statistical-models10
neuroimaging10
jupyter-notebook10
bayesian-inference10
test-automation10
data-analysis10
testing9
probabilistic-programming9
Programming languages (11)
Github contributions (5)
neurosynth/neurosynth
Oct 2012 - Jan 2021
Neurosynth core tools
Role in this project:
Back-end Developer
Back-end DeveloperContributions:294 commits, 13 PRs, 68 pushes in 8 years 3 months
Contributions summary:Tal primarily contributed to the core tools of the neurosynth project, as indicated by changes to the dataset, base, analysis, and related files. The commits involved adding tests, bug fixes, and general improvements, with specific edits to the dataset loading, feature handling, and meta-analysis images. Further contributions include the development of decoding tools and functionalities to support a full meta-analysis and new methods such as co-activation.
neurosciencepythonsciencecomputational-neuroscienceneurons
pytransitions/transitions
Oct 2014 - Dec 2016
A lightweight, object-oriented finite state machine implementation in Python with many extensions
Role in this project:Back-end Developer
Back-end DeveloperContributions:159 commits, 50 PRs, 88 pushes in 2 years 2 months
Contributions summary:Tal contributed to the core logic and functionality of the Python state machine library. Their commits focused on refactoring and improving the core files of the project. The changes included removing dependencies, updating event state handling, improving state access, adding state change listeners, and implementing a testing suite. The user also added a setup script and made adjustments to the transition initialization process.
state-machinespythonfinite-statehierarchical-state-machinenested-states
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