ANR/DST Joint Call for Proposals: Applied Mathematics and Artificial Intelligence

A joint call for proposals to support collaborative projects involving French and Indian research teams on topics relating to artificial intelligence and applied mathematics. 

The Agence Nationale de la Recherche (ANR – National Research Agency) was first established in 2005 and is governed by the French Ministry of Research. It provides funding to public research organisations and universities, as well as to private companies, for both basic and applied research in all fields of science. Its goals include promoting creativity and openness as well as new ideas and partnerships, in particular between academia and industry. It also seeks to improve the competitiveness of French research in Europe and around the world.  

At the second meeting of the Franco-Indian Joint Committee for Science and Technology (JCST) in Delhi in June 2024, ANR and India’s Department of Science and Technology (DST) agreed to launch a series of joint calls between France and India in order to intensify scientific collaboration between the two countries. Following the completion of a call for proposals on green hydrogen launched in 2025, the two organisations have come together again for a new call for proposals, this time focused on applied mathematics and artificial intelligence (AI).

The aim of the call is to consolidate Indo-French research networks in these fields and to create new networks. Both organisations are aiming to fund innovative, binational projects with strong synergy between teams from both countries and effective integration of joint research. Partners will work together as a joint team with complementary competencies in one common project, creating a joint output. 

Proposals are welcome on the following thematic areas:

• Mathematical foundations of AI
  • Geometric approaches and geometry of information for AI.
  • Algebraic and formal modelling for AI, low-rank matrix decomposition and tensor decomposition.
  • Stochastic modelling and AI, and statistical evaluation (stochastic processes, random matrices etc).
  • Analytical approaches.
  • Limits and safeguards on the behaviour of large-scale AI systems.
• Theoretical foundations of optimisation and AI
  • Assisted optimisation and control via AI.
  • Optimisation in the context of AI.
  • Fundamental limits of AI.
  • Optimal transport theory.
  • Automatic differentiation.
  • Multi-agent environments.  
• Mathematics for safe, trustworthy and reliable AI
  • Interpretability and explicability of AI systems.
  • Equity of solutions proposed by AI tools.
  • Quantification of incertitude in the context of AI solutions.
  • Energy sobriety.
• AI modelling for partial differential equations (PDEs) and PDEs modelling for AI
  • Digital analysis enriched by AI methods.
  • PDE modelling of neural networks.
  • Control enriched by learning and learning enriched by control.
  • Study of stochastic PDEs using AI.
  • Neuronal PDEs and neuron networks inspired by PDEs. 

Even if at the early stages of research, all projects must consider issues related to environmental and socioeconomic impacts if relevant to the research topic.

As both countries are seeking to encourage researchers’ mobility and knowledge exchange between France and India, consortia are encouraged to include concepts for integrated collaboration between partners from both countries, as well as plans for cross-border networking (eg regular meetings of participating groups, joint workshops, staff exchanges across organisations, joint publications, visas, medical insurance etc).