Podcast thumbnail for Poincaré Podcast

Poincaré Podcast

Claim This Podcast

by Poincaré Trajectories

5.0(5 reviews)
26 episodes
Updated Daily
Accepts GuestsHas Sponsors

Podcast Overview

Research podcast. Infinitely differentiable. Podcast cover art: Order-7 triangular tiling.

Language

🇺🇲

Publishing Since

2/19/2022

1 verified contact email on file for Poincaré Podcast

Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.

Recent Episodes

Episode thumbnail for Poincaré Podcast #26 - Logan Kilpatrick

July 26, 2022

Poincaré Podcast #26 - Logan Kilpatrick

<p>In this episode, we interview Logan Kilpatrick. Logan currently splits his time between a number of professional commitments he is passionate about. He is a full-time Senior Technology Advocate at PathAI, the Developer Community Advocate for the Julia Programming Language, and a Teaching Fellow for Harvard University's Extension School course CSCI E-33A.<br> Logan was previously an Applied Machine Learning Engineer and Software Engineer at Apple as well as the Community Manager for the Julia Programming Language. Additionally, Logan is on the Board of Directors at NumFOCUS and DEFNA. We started talking about the whole Julia Ecosystem with a particular focus on their pandemic response, touching a bit on the hot theme of the Metaverse. We spoke about why someone should use Julia with respect to other programming languages, mentioning some specific packages. We then switch to decentralisation/open source topics analyzing them ideologically, applicationally and financially. We then talked about Julia's future and the amazing interactions among Julia users. Given the background of Logan, we finally spoke about open science with NASA and the application of Julia in the aerospace sector, speaking also about PathAI, Logan's full-time company job.</p> <p>LINKS:<br> <a href="https://julialang.org" target="_blank">https://julialang.org</a><br> <a href="https://github.com/logankilpatrick" target="_blank">https://github.com/logankilpatrick</a><br> <a href="https://twitter.com/OfficialLoganK" target="_blank">https://twitter.com/OfficialLoganK</a><br> <a href="https://scholar.harvard.edu/logankilpatrick" target="_blank">https://scholar.harvard.edu/logankilpatrick</a></p> <p>RESOURCES:<br> Anchor: <a href="https://anchor.fm/poincare-podcast" target="_blank">https://anchor.fm/poincare-podcast</a><br> Youtube: <a href="https://www.youtube.com/watch?v=l2I45GqREgE&amp;list=PLQIbxjHCZG-BUTCC5tdGUjtx23EQGebAw&amp;index=13" target="_blank">https://www.youtube.com/watch.v</a><br> RSS: <a href="https://anchor.fm/s/84561ce0/podcast/rss" target="_blank">https://anchor.fm/s/84561ce0/podcast/rss</a><br> Linktree: <a href="https://linktr.ee/poincaretrajectories" target="_blank">https://linktr.ee/poincaretrajectories</a><br> Company: <a href="https://www.linkedin.com/company/poincaretrajectories/" target="_blank">https://www.linkedin.com/company/poincaretrajectories/</a></p> <p></p>

Episode thumbnail for Poincaré Podcast #25 - Erik Van Winkle

July 21, 2022

Poincaré Podcast #25 - Erik Van Winkle

<p>Here is a conversation with Erik Van Winkle, Operations Lead at DeSci Labs, besides having been part of the core team at Constitution DAO.<br> DeSci is a pioneering movement dedicated to exploring the capabilities of web3 technologies applied to the scientific ecosystem. We started talking about how DeSci works and the potential of sharing information while maintaining copyright. Then we jumped into the differences between decentralized science and open source, touching on the system design and business models. We then spoke about the story of DeSci and its relevant implementation choices. We finally discussed the new paradigm brought by DeSci, focusing on the ethics of interacting with traditional scientific media.</p> <p>LINKS:<br> <a href="https://www.linkedin.com/in/erik-van-winkle/" target="_blank">https://www.linkedin.com/in/erik-van-winkle/</a><br> <a href="https://desci.com/" target="_blank">https://desci.com/</a><br> <a href="https://discord.gg/TnTsAUUu" target="_blank">https://discord.gg/TnTsAUUu</a><br> <a href="https://t.me/BlockchainForScience" target="_blank">https://t.me/BlockchainForScience</a></p> <p>RESOURCES:<br> Anchor: <a href="https://anchor.fm/poincare-podcast" target="_blank">https://anchor.fm/poincare-podcast</a><br> Youtube: <a href="https://www.youtube.com/watch?v=l2I45GqREgE&amp;list=PLQIbxjHCZG-BUTCC5tdGUjtx23EQGebAw&amp;index=13" target="_blank">https://www.youtube.com/watch.v</a><br> RSS: <a href="https://anchor.fm/s/84561ce0/podcast/rss" target="_blank">https://anchor.fm/s/84561ce0/podcast/rss</a><br> Linktree: <a href="https://linktr.ee/poincaretrajectories" target="_blank">https://linktr.ee/poincaretrajectories</a><br> Company: <a href="https://www.linkedin.com/company/poincaretrajectories/" target="_blank">https://www.linkedin.com/company/poincaretrajectories/</a></p> <p></p>

Episode thumbnail for Poincaré Podcast #24 - Jean-Marc Mercier

July 12, 2022

Poincaré Podcast #24 - Jean-Marc Mercier

<p>The guest of this episode is Jean-Marc Mercier. Dr. Jean-Marc studies machine learning, both kernel methods and deep learning, in the context of mathematical finance.<br> We start talking about the differences between kernel methods and deep learning and some history of machine learning, then about the relations between orthogonal polynomials, and deep learning and kernel methods, touching on the application of kernel principal component analysis in aerospace and optimal transport. Dealing with finance, we talk about his vision in AI algorithmic trading and in general more financial applications where AI can be useful. Then we move on modelling approach and assumptions of the observable that brought us to economic bubble formation. We reserve quite a lot of time to talk about "codpy" an open-source python library for machine learning, mathematical finance and statistics of which Jean-Marc is one of the authors. We end up speaking about "codpy" more in detail such as function representation, mesh free methods which bring us to its applicability in fluid dynamics and we conclude with the future expansions of this library.</p> <p>LINKS:<br> <a href="https://www.researchgate.net/profile/Jean-Marc-Mercier" target="_blank">https://www.researchgate.net/profile/Jean-Marc-Mercier</a><br> <a href="https://pypi.org/project/codpy/" target="_blank">https://pypi.org/project/codpy/</a></p> <p>RESOURCES:<br> Anchor: <a href="https://anchor.fm/poincare-podcast" target="_blank">https://anchor.fm/poincare-podcast</a><br> Youtube: <a href="https://www.youtube.com/watch?v=l2I45GqREgE&amp;list=PLQIbxjHCZG-BUTCC5tdGUjtx23EQGebAw&amp;index=13" target="_blank">https://www.youtube.com/watch.v</a><br> RSS: <a href="https://anchor.fm/s/84561ce0/podcast/rss" target="_blank">https://anchor.fm/s/84561ce0/podcast/rss</a><br> Linktree: <a href="https://linktr.ee/poincaretrajectories" target="_blank">https://linktr.ee/poincaretrajectories</a><br> Company: <a href="https://www.linkedin.com/company/poincaretrajectories/" target="_blank">https://www.linkedin.com/company/poincaretrajectories/</a></p> <p></p>

26 total episodes available

Deep-dive analytics for Poincaré Podcast

Frequently asked questions

Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.

What is Poincaré Podcast?

Research podcast. Infinitely differentiable.

Podcast cover art: Order-7 triangular tiling.

How often does this podcast release new episodes?

This podcast updates daily.

Where can I listen to this podcast?

This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.

Does this podcast accept guests?

Yes, this podcast regularly features guests.

Legal Disclaimer

Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.

All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.

We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.

While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.

By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.