IRIF, the Research Institute on the Foundations of Computer Science, is a research laboratory of CNRS and université Paris-Diderot, also hosting two INRIA project-teams.

The research conducted at IRIF is based on the study and understanding of the foundations of all computer science, in order to provide innovative solutions to the current and future challenges of digital sciences.

IRIF hosts about 200 people. Six of its members have been distinguished by the European Research Council (ERC), three are members of the Institut Universitaire de France IUF), and two are members of the Academia Europæa.


Three papers coauthored by IRIF members will be presented at the prestigious conference LICS'19 in Vancouver this summer. Topics include sequent calculus, differential logic and probabilistic computation.

The Spring session of Graph Theory in Paris will be held on Friday April 26 at Amphi Turing. Speakers of the event: Penny Haxell from U. Waterloo and Patrice Ossona de Mendez from CNRS.

Sergio Rajsbaum from Universidad Nacional Autonoma de Mexico, a world-renowned expert in the theory of distributed computing, is visiting IRIF from March 31st to May 2nd.
Distributed systems

Distributed systems are groups of networked computers, interacting with each other in order to achieve the same goal. In parallel computing, all processors have access to a shared memory to exchange information between processors. In distributed computing, information is exchanged by passing messages between the processors. Cluster of computers and peer-to-peer systems are examples of such architectures. Models of distributed systems are also used in other science, such as in biology, in order to analyze collective behaviors of autonomous entities interacting with each other by message passing.
Uri Zwick

From March 20th to May 22nd, Uri Zwick (Univ. of Tel Aviv) will give a series of 7 courses related to his FSMP Chaire of Excellence on the topic of Games on Graphs and Linear Programming Abstractions each Wednesday 2:15pm - 4:15pm at IRIF, room 3052.
Linear programming

Linear programming is a technique for the optimization of a linear function, subject to linear equality and linear inequality constraints. A linear programming algorithm finds a point in the polyhedron of feasible solutions satisfying those constrains, where this function has the smallest (or largest) value. Linear programming is widely used in industries, including transportation, energy, telecommunications, and manufacturing, for diverse types of tasks such as planning, routing, scheduling, assignment, and design.

Iordanis Kerenidis (IRIF) explains what we can expect from Quantum Computing in this interview of the CNRS journal.

Ali Charara, director of INS2I at CNRS, visits IRIF on the morning of April 24th. The research conducted at IRIF will be presented as well as 6 specific scientific talks. The visit will be followed by a light buffet lunch.

Université Paris Diderot has opened several teaching assistant positions (ATER) in Computer Science on the research topics of IRIF. Deadline to apply : May 6, 2019.

Ile de France

The Paris Region PhD2 program will grant 30 PhD projects on Digital Sciences and with an industrial partner. IRIF is an eligible hosting lab. Call for application is open until May, 15th 2019.

(These news are displayed using a randomized-priority ranking.)

Limited number of events during the Spring break

Proofs, programs and systems
Thursday May 2, 2019, 10:30AM, Salle 3052
Hugo Férée (University of Kent) Une théorie de la complexité d'ordre supérieur via la sémantique des jeux

Alors que de nombreux modèles de calcul nous permettent de manipuler des données issues de domaines non dénombrables (fonctions d'ordre supérieur, nombres réels, objets définis par co-induction), les différentes notions de complexité ne permettent de s'intéresser qu'à des fonctions d'ordre 1 (i.e. traitant des données finies) voire des fonctions d'ordre 2 (i.e. traitant des fonctions d'ordre 1). Dû à la difficulté de définir une notion pertinente de taille pour des données d'ordre quelconque, les notions de complexité pour des fonctions d'ordre 3 ou plus sont à la fois incomplètes et imparfaites.

En nous appuyant sur la sémantique des jeux nous proposons ici une définition de taille et de complexité pour les fonctions d'ordre supérieur de PCF, et plus généralement pour tout processus calculatoire assimilable à une certaine classe de jeux séquentiels.