[Online] Google Summer of Code (GSOC) Experience

## How to join the webinar

NOTE: You can join via your browser (no app download required). Use Chrome or Firefox.
Pre-register for the webinar:
https://www.bigmarker.com/neo4j/Data-Umbrella-Webinar

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Video Recording
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This event will be recorded and placed on our YouTube. We usually have it up within 24 hours of the event. Subscribe to our YouTube and set your notifications:
https://www.youtube.com/c/DataUmbrella/

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Time
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9am PT / 12pm ET / 8pm EAT / 10:30 pm IST

## Speakers

Tirth Patel, Larry Dong and Oriol Abril Pla

## Talk Level

Beginner

## Pre-reqs

None

## Prep Work

None

## Resources

• GSOC website: https://summerofcode.withgoogle.com/
• Application timeline: https://developers.google.com/open-source/gsoc/timeline

## Event

Google Summer of Code (GSoC) is a global, online program focused on bringing new contributors into open source software development. GSoC Contributors work with an open source organization on a 12+ week programming project under the guidance of mentors.
GSOC 2023 application begins in January 2023.

In this panel discussion, we speak with several GSOC alumni of the PyMC project to learn of their experiences including the application process, mentorship experience and post-GSOC open source participation.

## Speaker

Tirth Patel is a maintainer of SciPy and a contributor to a few other open-source projects like NumPy, PyMC, and scikit-learn. He participated in Google Summer of Code with PyMC in 2020 and with SciPy in 2021. He works primarily with Python and C, and he also codes with C++ and Julia. He is currently a graduate computer science student at Arizona State University.

GitHub: https://www.github.com/tirthasheshpatel
LinkedIn: https://www.linkedin.com/in/tirthasheshpatel/

Larry Dong is a PhD student in biostatistics at the Dalla Lana School of Public Health at the University of Toronto in Toronto, Canada. His academic interests revolve around dynamic treatment regimes and Bayesian methods. He began his PhD during the pandemic which has allowed him to be immersed in open-source, particularly in the PyMC community. His first GSoC project entailed implementing a Dirichlet Process submodule for PyMC and he returned for another GSoC to continue this project and to learn more about Aesara and AePPL.
Website: http://larrydong.com/
GitHub: https://github.com/larryshamalama
LinkedIn: https://www.linkedin.com/in/larry-dong/
Twitter: https://twitter.com/larryshamalama
Mastodon: https://fosstodon.org/@larryshamalama

Oriol has a background in engineering physics and astrophysics and currently works as a computational statistician. He is a core contributor and council member of ArviZ and PyMC projects. He has also worked on statistical research while at Helsinki University and Universitat Pompeu Fabra (Barcelona), especially in the fields of inference diagnostics, prior elicitation and data visualization.
Oriol dedicates a lot of his time to community management and documentation because he believes they are as important as the code. He has helped organize and mentored in multiple Data Umbrella sprints. He has also mentored many new ArviZ and PyMC team members whose backgrounds ranged from computational scientist to technical writer.

Website: https://oriolabrilpla.cat/en/
GitHub: https://github.com/OriolAbril
Twitter: https://twitter.com/OriolAbril
Mastodon: https://toot.cat/@oriolabril
LinkedIn: https://www.linkedin.com/in/oriol-abril-pla-1b9123180/

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