Created in 2020, INSIMIA brings together the CNRS, the University of Montpellier and the Politecnico di Torino.
International Research Projects (IRP)
An IRP is a collaborative research project set up by one or more CNRS laboratories and laboratories from one or two other countries.
These projects enable the consolidation of established collaborations through short- or medium-term scientific exchanges. Their aims are to organise work meetings or seminars, develop joint research activities including field research and finally to supervise students. Teams from France and other countries must have already proved they are able to collaborate together, for example through one or more joint publications. IRPs last for five years. CNRS Informatics currently has 12 IRPs which correspond to strategic international collaborations.
AAURS in Australia
The goal of the creation of the IRP Advancing Autonomy for Unmanned Robotic Systems (AAURS) between the laboratory Informatique, Signaux et Systèmes de Sophia-Antipolis (I3S - CNRS/Université Côte d'Azur) and the Australian National University Research School of Engineering is to go beyond the state of the art in systems theory and control applied to unmanned robots. Many open theoretical problems with high impact in practical applications will be addressed to enable unmanned robotic systems to operate more reliably in complex dynamics. For example, attention is paid to environments encountered in real-world applications.
ADONIS in Lebanon
The Intelligent Systems Diagnostics and Control Approaches IRP (ADONIS), 2020-2025, focuses on intelligent systems diagnostics and control. It brings together researchers from four partner organizations: Compiègne University of Technology (UTC), Faculty of Engineering – Lebanese University (UL), CNRS France and CNRS Lebanon, with common interests and a willingness to collaborate in the areas of control, data analysis, control of uncertainties and this in several frameworks of studies, such as in particular biomedical systems and transport systems. Three UTC/CNRS research units are involved in this IRP: Heuristics laboratory and diagnosis of complex systems (Heudiasyc - CNRS/Université de technologie de Compiègne), Roberval laboratory - Mechanical, acoustic and materials research unit (Roberval - CNRS/Université de technologie de Compiègne) and the Biomechanics and Bioengineering Laboratory (BMBI - CNRS/Université de technologie de Compiègne).
After many years of collaboration between these institutions, and particularly between UTC and UL since 1997, this project aims to consolidate and sustain this collaboration, to broaden its scope to new research themes, and increase its attractiveness and visibility.
See also: "Sustain and amplify Franco-Lebanese scientific collaboration"
APIER in Greece
One of the major current challenges in child-robot interaction within an educational framework is to enable effective and beneficial interactive learning over time. The robot must adapt online to different children and their progress. In return, the child should advance in their learning through interaction with the robot. The aim of this IRP, led by the Institut des systèmes intelligents et de robotique (ISIR – CNRS/Sorbonne University), is to strengthen a partnership with the Polytechnic University of Athens. In recent years, ISIR researchers have pioneered the implementation of online learning capabilities in humanoid robots during interactions with typically developing children or those with autism spectrum disorders. The goal now is to demonstrate that this provides a significant long-term educational benefit compared to pre-programmed robots.
GeoGen3DHuman in Italy
The Geometric Deep Learning and Generative Models for 3D Human IRP (GeoGen3DHuman) between Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL - CNRS/Université de Lille/ Centrale Lille) and the Media Integration and Communication Center (MICC) is a joint research and collaboration in the area of Computer Vision and Artificial Intelligence. The core of GeoGen3DHuman is on developing mathematically principled generative frameworks for deep learning on non-Euclidean domains such as graphs and 3D meshes. GeoGen3DHuman touches upon some of the most challenging problems in different fields such as computer vision and graphics, where generative models are very crucial. The research topic itself is very timely in terms of need and applicability of the systems targeted. This research also seeks to advance fundamental tools, that are not only of high relevance in terms of intellectual merit but also in broad impact.
Specifically, it develops techniques for geometric deep learning on 3D meshes, generative models in non-Euclidean domains and applications that use 3D models of the face and of the human body
Keywords: artificial intelligence, geometric deep learning, 3D/4D human.
INSIMIA in Italy
The IRP Integrity of Hardware- Software Embedded Systems
in the age of Artificial Intelligence (INSIMIA) is the continuation of the project initiated with the Franco-Italian Laboratory for Research on Integrated Hardware-Software Systems (Lafisi) which allowed to establish the visibility of the LIRMM and the Politecnico di Torino in the field of testing and reliability integrated hardware-software systems, notably through consistent and high-quality scientific production. INSIMIA aims to boost the synergy between these two centres developing complementary research, to develop new research themes in the field of the integrity of integrated systems on chip, but in a research space centered on Artificial Intelligence. Particular attention shall be paid to the exploitation and technology transfer of the research results obtained under this IORP.
JMSL in the USA
The Joint Montpellier Stanford Laboratory (JMSL) is a partnership between the Montpellier Laboratory of Computer Science, Robotics and Microelectronics (LIRMM - CNRS/Université de Montpellier) and Stanford University. Its objective for the coming years is based on collaborations based on the three main axes presented below:
• underwater robotics,
• medical robotics,
• semantic web.
Ultimately, this collaboration aims to expand to other topics such as human-robot interactions, biomedical applications, data science, etc.
MAKC in the USA
The Modern Approaches to Knowledge Compilation IRP (MAKC) is centered on knowledge compilation (KC) for problem solving. KC is a research area which aims to preprocess information to improve the time required to solve highly-demanding computational tasks (i.e., solving NP and Beyond NP problems). The main objective of MAKC is to conceive and evaluate KC tools of various kinds (mainly preprocessors, compilers and reasoners) and to apply them to solve problems from a large spectrum of areas, for instance product configuration, formal verification, probabilistic inference, machine learning, and databases.
Keywords: artificial intelligence, deep solving, knowledge compilation
MLNS2 in Cameroon
The IRP Machine Learning, Network, System and Security (MLNS2) is interested in cybersecurity, which is a crucial research topic both in Cameroon and in France. It's mainly interested in two problems: the proliferation of malware on smartphones and phone call fraud that several African countries suffer from.
Created in 2022, MLNS2 associates in France CNRS and several laboratories namely Laboratoire d'Informatique en Images et Systèmes d'Information (LIRIS - CNRS/INSA de Lyon/Université Claude Bernard Lyon 1), Laboratoire d’Informatique de Grenoble (LIG, CNRS/Université Grenoble Alpes), Institut de recherche en informatique et systèmes aléatoires (IRISA - CNRS/Université de Rennes 1), and in Cameroon the University of Yaoundé I and its computer science laboratories.
Keywords: security, operating system, machine learning, networks, privacy.
ROI-TML in Canada
The IRP Operational Research and Informatics in Transport, Mobility and Logistics (ROI-TML) is interested in optimization problems (discrete and/or continuous) resulting from modern and sustainable transport, combining the movement of goods and the mobility of people.
Created in 2016, ROI-TML brings together the CNRS and the University of Valenciennes Hainaut-Cambrésis for the Laboratory of Industrial and Human Automatic, Mechanical and Computer Science (LAMIH - CNRS/Université Valenciennes Hainaut-Cambrésis), and the Centre interuniversitaire de recherche sur les réseaux d'entreprise, la logistique et le transport (CIRRELT - Université de Montréal).
SINFIN in Argentina
The research carried out within the framework of the IRP Systems, Verification, Fundamental Training, LogIque, Statistics (SINFIN) focuses on the use of formal methods in the implementation of theories and automatic tools for modelling, verification and development of complex software.
Created in 2019, SINFIN succeeds the LIA Infinis which started in 2011. It associates the CNRS, the Université Paris Diderot, the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and the University of Buenos Aires.
Keywords: fundamental computing, Logic, Languages, Verification and Systems
The Trójkąt in Poland
Warsaw, Paris, and Bordeaux are major research centers in automata theory, logic, and game theory. The InternIRP) Le Trójkąt aims to structure and develop these collaborations, strengthening the historical ties between France and Poland in these fields. Since the 1990s, figures like Damian Niwinski, Igor Walukiewicz, and André Arnold have significantly contributed to these exchanges. Recent successes include solving complex problems such as the complexity of reachability in Petri nets and parity games, thanks to the work of researchers from the University of Warsaw, the l'Institut de recherche en informatique fondamentale (IRIF - CNRS/University of Paris) in Paris, and the Laboratoire bordelais de recherche en informatique (LaBRI - CNRS/Bordeaux INP/University of Bordeaux) in Bordeaux. The IRP Le Trójkąt seeks to expand these collaborations beyond the Paris-Bordeaux-Warsaw triangle, involving other institutions in France and Poland. Through organizing scientific events and supporting research, the project fosters cooperation to tackle major challenges in fundamental computer science.