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What is CRI?

CRI is co-constructing and sharing new ways of learning, teaching, conducting research and mobilizing collective intelligence in the fields of life, learning and digital sciences, in order to address the UN's sustainable development goals (SDGs).

CRI operates around 4 main areas :

  • Developing and hosting educational programs, from preschool to high school (Savanturiers - École de la Recherche), interdisciplinary Bachelor, Master, and PhD (EURIP Graduate School) as well as lifelong learning degree programs of the Université de Paris.
  • Conducting research within its INSERM-Université de Paris research Collaboratory Unit, advised and guided by a Scientific Advisory Board, composed of prestigious international scientific leaders.
  • Developing the #LearningPlanet initiative in partnership with UNESCO, of which it also holds a Chair, and AFD to inspire and empower learners of all ages who wish to identify, develop and amplify the most effective ways to learn how to solve problems together.
  • Building a living campus where innovative makers can set up digital infrastructures for learning communities to help them to resolve global challenges.

CRI was founded in 2006 by François Taddei and Ariel Lindner with the Bettencourt Schueller Foundation as an essential and key supporting partner and Paris City Hall. It also benefits from the support of a wide range of foundations, corporate sponsors and institutions including the University of Paris, with which CRI co-founded the interdisciplinary action-based research challenge institute (“Institut des Défis”) to prototype a model of a Learning University enable of responding to the global challenges of our time.

  • 350 students each year, 1300 students since CRI's creation
  • +40 research fellows
  • +30 000 pupils involved in Savanturiers program since Savanturiers' creation in 2013
  • +100 talks by international scientific leaders
  • +100 000 subscriptions to CRI’s MOOCs since 2014
  • +50 nationalities
Save the date
Monday, December 7, 2020
9:30 AM
Bifurcations dans l'apprentissage - Workshop 3 -

La Biennale internationale du design 2021 à Saint-Etienne a pour titre BIFURCATIONS. Le CRI est co-auteur de la conception et de la réalisation de BIFURCATIONS DANS L'APPRENTISSAGE, une des grandes expositions qui a la particularité d'être produite par les étudiants de l'ESADSE . Durant cette troisième semaine de workshop créatif, les étudiants définissent la scénographie, les gabarits des espaces de l'exposition et imaginent l'atmosphère dans laquelle se déroulera le parcours des visiteurs. Ce workshop a lieu à Saint-Etienne, dans les locaux de l'école et de la Cité du design, dans l'ancienne manufacture d'armes de Saint-Etienne. Il commencera avec l'exploration des magasins de l'école et de la ville pour choisir le matériel de réemploi qui est à la base de la scénographie. Il continuera avec le dessin et la production de maquettes de l'exposition ... Le groupe est encore ouvert, les délais sont courts et tous les talents sont bienvenus, qu'il s'agisse de scénographie, de participation aux conférences, de contenu pour l'exposition. Si vous êtes intéressé.e.s par le thème, et par le procédé de production collective par des étudiants, parlons-en ! Au CRI deux personnes sont principalement à votre écoute sur le sujet : Marguerite Benony, cheffe de projet, Sophie Pène, Co-commissaire de l'exposition, avec Olivier Lellouche (Esadse) toutes les deux joignables à l'adresse prénom.nom@cri-paris.org

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Monday, December 7, 2020
11:30 AM
CRI Research Seminar: Remy Kusters

Deep learning driven model discovery in biology and physics

In this talk I will introduce DeepMoD, a deep learning based model discovery algorithm which seeks the partial differential equation underlying a spatio-temporal data set. DeepMoD employs sparse regression on a library of basis functions and their corresponding spatial derivatives. A feed-forward neural network approximates the data set and automatic differentiation is used to construct this function library and perform regression within the neural network.We illustrate this approach on several problems in the context of (bio)physics, mechanics and fluid dynamics, such as the Burgers', Korteweg-de Vries, advection-diffusion and Keller-Segel equations, and find that it requires as few as O(100) samples and works at noise levels up to 75%. This resilience to noise and high performance at very few samples allows to apply DeepMoD directly to noisy experimental time-series data, discovering e.g. the advection diffusion equation from a gel electrophoresis experiment.

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Thursday, December 10, 2020
5:00 PM
Network reconstruction from indirect observations

Happy to invite you for the network seminar with Tiago P. Peixoto. The talk will be online, please register to receive the link!

Network reconstruction from indirect observations

The observed functional behavior of a wide variety of large-scale systems is often the result of a network of pairwise interactions. However, in many cases these interactions are hidden from us, either because they are impossible or very costly to be measured directly, or, in the best case, are measured with some degree of uncertainty. In such situations, we are required to infer the network of interactions from indirect information.

In this talk, I present a scalable Bayesian method to perform network reconstruction from indirect data, including noisy measurements and observed network dynamics. This kind of approach allows us to convey in a principled manner the uncertainty present in the measurement, and combined with versatile modelling assumptions can yield good results even when data are scarce. In particular, I describe how the reconstruction approach can be combined with community detection, allowing us to tap into multiple sources of evidence available for the task. I show how this combined approach provides a twofold improvement, by increasing not only the reconstruction accuracy, but also the identification of communities in networks. The latter improvement is possible even in situations where at first we might imagine that reconstruction is superfluous, for example when direct network data are available and measurement errors can be neglected.

Bio: Tiago P. Peixoto is an Associate Professor at the Department of Network and Data Science at the Central European University https://networkdatascience.ceu.edu/people/tiago-peixoto His research focuses on characterizing, identifying and explaining large-scale patterns found in the structure and function of complex network systems — representing diverse phenomena with physical, biological, technological, or social origins — using principled approaches from statistical physics, nonlinear dynamics and Bayesian inference. Peixoto develops and maintains graph-tool — an efficient Python module for manipulation and statistical analysis of graphs and networks. He has a PhD in Physics from the University of São Paulo, and a Habilitation in Theoretical Physics from the University of Bremen. In 2019 he was the recipient of the Erdős–Rényi Prize in Network Science, awarded by the Network Science Society.

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Monday, December 14, 2020
11:30 AM
CRI Research Seminar: Raúl Velasco-Fernández

Depoliticizing and repoliticizing SDGs

Sustainable Development Goals (SDGs) have become an important political reference for all types of institutions as public administration, multinationals or NGOs. The advocates of SDGs emphasize that they are the result of a deliberative and decision-making process building on expert knowledge and considering a plurality of moral arguments about human dignity, achieving a discursive consensus with strong universalist legitimacy. However, they have been accused to be a political instrument for imposing “green-economy” under a neoliberal agenda (e.g. fostering land-grabbing), ignoring that sustainability requires the reduction of consumption of the richest and redistribution, and not just a change in the so-called Knowledge-based Bio-Economy. In this seminar, we will discuss: (i) how ignoring the systemic contradictions among SDGs when implementing specific policies contribute to the growing distrust in institutions; (ii) how depoliticising for maintaining consensus is a bad solution to handle conflicts derived from SDGs agenda; (iii) the fact that the identification of the concerns addressed by SDGs has been based on deliberative processes, does not exclude that at the moment of prioritizing policies a hegemonic perspective of perpetual economic growth is adopted; (iv) the implementation of SDGs policies would require not only a deliberative process identifying priorities over concerns but also the recognition of their conflictive nature. Therefore, this process should leave the door open to a continuous re-adjustment of both the list of concerns and the priorities over them. In conclusion, the quality check over SDGs policies should be used to repoliticise their discussion.

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Sunday, January 10, 2021
9:30 AM
Visite du centre de tri des déchets - Visit the sorting facilities (Reported)

English below

La société Cèdre est une entreprise sociale et solidaire en charge de nos collecter et valoriser nos déchets. Nous vous proposons de visiter leur centre de tri afin de mieux comprendre l'importance du tri sélectif.

Vous aurez l'occasion de découvrir leur organisation et la logistique mise en oeuvre pour valoriser au mieux ces ressources, notamment :

Le tri du papier et des contenants boissons Les normes environnementales en vigueur La tracabiltié des déchêts Les bénéfices environnementaux L'accompagnement social des personnes en situation de handicap

The company Cèdre is a social and solidarity enterprise in charge of collection and recovery of our waste. We invite you to visit their sorting center to better understand the importance of selective sorting.

You will have the opportunity to discover their organization and the logistics implemented to make the best use of these resources, in particular:

Sorting paper and beverage containers Environmental standards in force The traceability of waste Environmental benefits Social support for people with disabilities
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