# Organizers ## Data Umbrella Organizers ::::{grid} 2 2 3 5 :gutter: 3 :::{grid-item} :class: sd-text-center Reshama Shaikh Reshama Shaikh [{fas}`globe`][reshama_web] [{fab}`github`][reshama_github] [{fab}`twitter`][reshama_twitter] [{fab}`linkedin-in`][reshama_linkedin] ::: :::{grid-item} :class: sd-text-center Beryl Kanali Beryl Kanali [{fab}`twitter`](https://twitter.com/BerylKanali) [{fab}`linkedin-in`](https://www.linkedin.com/in/beryl-kanali-260567185/) ::: :::{grid-item} :class: sd-text-center Sandra Meneses Sandra Meneses [{fab}`github`](https://github.com/symeneses) [{fab}`linkedin-in`](https://www.linkedin.com/in/symeneses/) ::: :::{grid-item} :class: sd-text-center Sandy Weng Sandy Weng [{fab}`linkedin-in`](https://www.linkedin.com/in/sandy-weng-a0959762) ::: :::{grid-item} :class: sd-text-center Cristina Mulas Cristina Mulas Lopez [{fab}`linkedin-in`](https://www.linkedin.com/in/cristina-mulas-00321a167/) ::: :::: ## PyMC Organizers ::::{grid} 2 2 3 4 :gutter: 5 :::{grid-item} :class: sd-text-center Christian Luhmann Christian Luhmann [{fas}`briefcase`][christian_work] [{fab}`twitter`][christian_twitter] ::: :::{grid-item} :class: sd-text-center Reshama Shaikh Reshama Shaikh [{fas}`globe`][reshama_web] [{fab}`github`][reshama_github] [{fab}`twitter`][reshama_twitter] [{fab}`linkedin-in`][reshama_linkedin] ::: :::{grid-item} :class: sd-text-center Oriol Abril Pla Oriol Abril Pla [{fas}`globe`](https://oriolabrilpla.cat) [{fab}`github`](https://github.com/oriolabril) [{fab}`twitter`](https://twitter.com/oriolabril) ::: :::{grid-item} :class: sd-text-center Thomas Wiecki Thomas Wiecki [{fas}`globe`][thomas_web] [{fas}`briefcase`][thomas_work] [{fab}`github`][thomas_github] [{fab}`twitter`][thomas_twitter] ::: :::: ## PyMC Mentors ::::{grid} 2 2 3 4 :gutter: 5 :::{grid-item} :class: sd-text-center Christian Luhmann Christian Luhmann [{fas}`briefcase`][christian_work] [{fab}`twitter`][christian_twitter] ::: :::{grid-item} :class: sd-text-center Oriol Abril Pla Oriol Abril Pla [{fas}`globe`](https://oriolabrilpla.cat) [{fab}`github`](https://github.com/oriolabril) [{fab}`twitter`](https://twitter.com/oriolabril) ::: :::{grid-item} :class: sd-text-center Ravin Kumar Ravin Kumar [{fas}`globe`](https://ravinkumar.com/) [{fab}`github`](https://github.com/canyon289) [{fab}`twitter`](https://twitter.com/canyon289) ::: :::{grid-item} :class: sd-text-center Danh Phan Danh Phan [{fas}`globe`][danh_web] [{fab}`github`][danh_github] [{fab}`twitter`][danh_twitter] [{fab}`linkedin-in`][danh_linkedin] ::: :::{grid-item} :class: sd-text-center Christopher Fonnesbeck Christopher Fonnesbeck [{fab}`linkedin-in`](https://www.linkedin.com/in/christopher-fonnesbeck-374a492a/) ::: :::{grid-item} :class: sd-text-center Michael Osthege Michael Osthege [{fab}`linkedin-in`](https://www.linkedin.com/in/michael-osthege-7987a6130/) ::: :::{grid-item} :class: sd-text-center Alex Andorra Alexandre Andorra [{fab}`linkedin-in`](https://www.linkedin.com/in/aandorra-pollsposition/) ::: :::{grid-item} :class: sd-text-center Fernando Irarrázaval Fernando Irarrázaval [{fab}`github`](https://github.com/cuchoi) ::: :::: Additionally, we thank all the PyMC team members who contributed by reviewing pull requests and assisting with outreach as well as [NumFOCUS](https://numfocus.org) for their support. ## Community Contributors ::::{grid} 2 2 3 4 :gutter: 5 :::{grid-item} :class: sd-text-center Cristiin Maureira-Fredes Cristián Maureira-Fredes [{fab}`linkedin-in`](https://www.linkedin.com/in/cmaureir/) ::: :::{grid-item} :class: sd-text-center Lucy Jiminez Lucy Jiminez [{fab}`github`](https://github.com/LucyJimenez) [{fab}`linkedin-in`](https://www.linkedin.com/in/lucy-j/) [{fab}`twitter`](https://twitter.com/JimenezLucyJ) ::: :::: ## About PyMC and Data Umbrella [Data Umbrella](https://www.dataumbrella.org/) is a global community for underrepresented persons in data science. It is a fiscally hosted project of Open Collective, a registered 501(c)(3) non-profit based in California, USA. Data Umbrella: organizes online speaker series on data science and open source, organizes sprints / hackathons, curates resources on inclusive practices. All levels are welcome, beginners and experts. [PyMC](https://www.pymc.io) is a probabilistic programming package for Python that allows users to fit Bayesian models using a variety of numerical methods, most notably Markov chain Monte Carlo (MCMC) and variational inference (VI). Its flexibility and extensibility make it applicable to a large suite of problems. PyMC is a non-profit project under NumFOCUS. [reshama_web]: https://reshamas.github.io [reshama_github]: https://github.com/reshamas [reshama_twitter]: https://twitter.com/reshamas [reshama_linkedin]: https://www.linkedin.com/in/reshamas [christian_work]: https://www.stonybrook.edu/commcms/psychology/faculty/faculty_profiles/cluhmann [christian_twitter]: https://twitter.com/1010is10 [thomas_web]: https://twiecki.io [thomas_work]: https://www.pymc-labs.io/team/thomas-wiecki/ [thomas_github]: https://github.com/twiecki [thomas_twitter]: https://twitter.com/twiecki [danh_web]: https://danhphan.github.io [danh_github]: https://github.com/danhphan [danh_twitter]: https://twitter.com/danhpt [danh_linkedin]: https://www.linkedin.com/in/danhpt