Name: 20. Paris Women in Machine Learning & Data Science @CRI
Start: 2019-09-26T19:00:00+02:00
End: 2019-09-26T22:00:00+02:00
Location: Learning Planet Institute (ex Centre de recherches interdisciplinaires (CRI))

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REGISTRATIONS HERE ONLY
https://events.cri-paris.org/e/601/meetup-paris-women-in-machine-learning-data-science
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The Women in Machine Learning & Data Science (WiMLDS) Meetup aims to inspire, educate, regardless of gender, and support women and gender minorities in the field. We are back for our 20th edition!

All genders may attend our meetups.
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Agenda

19:00 – Introduction by CRI & the Paris WiMLDS team

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19:25 – “Reconstruction of ecological interaction networks” by Raphaëlle Momal-Leisenring, PhD Candidate in Applied Mathematics @AgroParisTech

Abstract: The behaviour of ecological systems mainly relies on the interactions between the species it involves. In many situations, these interactions are not observed and have to be inferred from species abundance data. Here is presented a generic statistical model for network reconstruction based on abundance data.

Twitter: https://twitter.com/MomalRaphaelle

19:45 – “From spatial complexity to real estate prices: statistical and stochastic models" by Sarah Soleiman-Halevy, PhD Candidate @MAEngineers

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20:10 – Panel discussion: Education: When Machine Learning Helps Human Learning

The panel discussion will be moderated by Marie Sacksick, PhD candidate @Domoscio

Panel participants :
Claude Terosier, CEO & Founder of Magic Makers
Bio: Claude Terosier founded Magic Makers in 2014 in Paris. Convinced that learning to code was a key to today’s world, she launched Creative Computing workshops for kids aged 7 to 17. Today, Magic Makers has reached over 15 000 kids, with 6 centers in Paris and Bordeaux, and teaches up to AI programming for teens.

Iryna Nikolayeva, Post-Doc Researcher
Bio: Iryna is a post-doctoral researcher in Sorbonne University. She is passionate about using data analysis to make education more captivating, efficient and humane. She is working on an adaptive learning tool for maths in middle school, and initiating the use of data analysis to improve education in my university.

Olivier Bory, CRI Health Lab Coordinator
Bio: Olivier is a resident in general medicine in Sorbonne University and founded the HealthLab in CRI. He is passionate about teaching how to understand and appropriate new technologies for practitioners. He is working on pedagogical explorations to learn how to teach machine learning for residents and health for data scientist, to improve technological solutions adapted to real need.

Gaele Regnault, CEO and Founder of LearnEnjoy
Bio: After 15 years of a promising international career in consultancy, industry and retail sectors, Gaele founded LearnEnjoy, and is now transforming the way France supports children with autism. With the LearnEnjoy team, Gaele fosters the use of innovative tools –apps, IA,…- and enable children to reach their full potential.

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20:45 – Networking / Cocktail

During the event, you can share content using #WiMLDSParis & @WiMLDS_Paris

After the meet-up, all the slides will be available on our Medium page : https://medium.com/@WiMLDS_Paris

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Host information :

Twitter - https://twitter.com/criparis
Website - https://cri-paris.org/

The auditorium can welcome 120 people.
Registrations here: https://events.cri-paris.org/e/601/meetup-paris-women-in-machine-learning-data-science
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Code of Conduct

WiMLDS is dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form. All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate.

Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate.

Thank you for helping make this a welcoming, friendly community for all. All attendees should read the full Code of Conduct before participating: https://github.com/WiMLDS/starter-kit/wiki/Code-of-conduct

Caroline Chavier

Chloe

Marina

ncernecka

Paris Women in Machine Learning & Data Science

Technology

Data Science

Data Mining

Machine Learning

Big Data

Open Source

Women in Technology

Data Management

Professional Women

Data Analytics

Data Visualization

Predictive Analytics

Artificial Intelligence

WiMLDS