Announcing PyBay2018’s Speakers!

PyBay2018 is only months away! We’re so excited to announce the list of speakers who will be presenting the main talks on August 17–19, 2018 in San Francisco, California.

First of all, thank you to everyone who’s taken the time to respond to our call for proposals.

Our goal was to curate a program that:

  • Includes the latest developments and use of Python in various fields
  • Is diverse and inclusive of everyone who’s passionate about Python and doing good things with it!

With a record number of amazing proposals and a limited number of slots this year, we had such a challenging time deciding talks. We’re pretty proud of what we’ve accomplished though, with a line-up of:

  • Seasoned speakers who’ve written popular Python libraries, CTOs of startups, developer evangelists from larger companies, a first timer who’s recently graduated from bootcamp, and everything in between
  • Perspectives from people living in the SF Bay Area, Los Angeles, WA, MA, OH, NE, TX, and 3 other continents
  • 25% of speakers are women
  • Excellent coverage on Python fundamentals and libraries, ML/AI/DS, DevOps/infrastructure. Some talks on performance, hardware, iOT and the people side of engineering too!

Here’s the final talk list, ordered by the speaker’s first name.

  1. Deprecating the state machine: building conversational AI with the Rasa stack — Alan Nichol
  2. Robots, biology and unsupervised model selection — Amelia Taylor
  3. Detecting business chains at scale with PySpark and machine learning — Andrew Danks
  4. Automated responses to questions about your health — Austin Powell
  5. Reproducible performance — profiling all the code, all the time, for free — Bartosz Wróblewski
  6. An import loop and a fiery reentry — Brandon Rhodes
  7. An absolute beginner’s guide to deep learning with Keras — Dr. Brian Spiering
  8. Diving into production issues at scale — Brian Weber
  9. Using JupyterLab with JupyterHub and Binder — Carol Willing
  10. Machine learning at Twitter: Twitter meets Tensorflow — Cibele Montez
  11. Bootstrapping a visual search engine — Cung Tran
  12. Airflow on Kubernetes: dynamically scaling Python-based DAG workflows — Daniel Imberman, Seth Edwards
  13. Ask Alexa: how do I create my first Alexa skill? — Darlene Wong & Varang Amin
  14. Finding Your Place in SRE and SRE in Your Place — David Blank-Edelman
  15. Using Keras & Numpy to detect voice disorders — Deborah Hanus
  16. How I learned to stop shell scripting and love the StdLib — Elaine Yeung
  17. How to read Python you didn’t write — Erin Allard
  18. Modern C extensions: why, how, and the future — Ethan Smith
  19. Tools to manage large Python codebases — Fabio Fleitas
  20. 1 + 1 = 1 or record deduplication with Python — Flávio Juvenal
  21. Clearer code at scale: static types at Zulip and Dropbox — Greg Price
  22. Docker for data scientists: simplify your workflow and avoid pitfalls — Jeff Fischer
  23. High-performance Python microservice communication — Joe Cabrera
  24. Zebras and lasers: a crash course on barcodes with Python — Jonas Neubert
  25. First steps to transition from SQL to pandas — Kasia Rachuta
  26. 2FA, WTF? — Kelley Robinson
  27. Finding vulnerabilities for free: the magic of static analysis — Kevin Hock
  28. Python services at scale — Lisa Roach
  29. Parse NBA statistics with Openpyxl — Lizzie Siegle
  30. Pull requests: merging good practices into your project — Luca Bezerra
  31. Amusing algorithms — Max Humber
  32. Production-ready Python applications — Michael Kehoe
  33. Serverless for data scientists — Mike Lee Williams
  34. Let robots nitpick instead of humans — Moshe Zadka
  35. Deploying Python3 application to Kubernetes using Envoy — Natalie Serebryakova
  36. How to make a multi-tenant microservice — Navin Kumar
  37. Building Google Assistant apps with Python — Paul Bailey
  38. Data science on geospatial data and climate change — Paige Bailey
  39. Building an AI-powered Twitter bot that guesses locations of pictures from pixels — Randall Hunt
  40. Why you need to know the internals of list and tuple — Ravi Chityala
  41. Django Channels and websockets in production! — Rudy Mutter
  42. Beyond accuracy: interpretability in “black-box” model settings — Sara Hooker
  43. How to instantly publish data to the internet with Datasette — Simon Willison
  44. Recent advances in deep learning and Tensorflow — Sourabh Bajaj
  45. Service testing with Apache Airflow — Zhangyuan Hu
  46. From batching to streaming: a challenging migration tale — Srivatsan Sridharan
  47. The bots are coming! Writing chatbots with Python — Wesley Chun
  48. asyncio: what’s next — Yury Selivanov

Please help us congratulate our PyBay 2018 speakers

Want to join in on the fun at 2018’s largest get-together of SF Bay Area Python devs? Grab your conference pass!

There are a few ways to get involved in making this conference even more awesome:

  1. Ask your company to join our amazing list of sponsors.
  2. Spread the word about PyBay 2018 on Twitter with #PyBay2018 and share this post!
  3. Share it out on your other social media and mailing lists.

Stay tuned for the talk schedule, pre-conference workshop lineup, diversity and inclusion drive, financial aid, volunteering opportunities, and more! We’ll be sharing more announcements here and on Twitter.

Once again, tremendous gratitude to everyone who’s taken the time to submit talk proposals. We’re amazed at the breadth and the depth of your knowledge!

Like what you read? Give Grace Law a round of applause.

From a quick cheer to a standing ovation, clap to show how much you enjoyed this story.