Mathematical Modeling, IT, and Physics Department - MMIP

President: Christophe Doursat
Vice-Presidents: Pierre Barbillon, Hayat Benkhelifa et Liliana Ibanescu
Administrative and Finance Manager: Sébastien Goussard
Secretary: Christelle Gehin

In a world in which digital technology is becoming increasingly prevalent—especially in the field of life and environmental sciences, where the phenomena being studied are becoming more complex—the MMIP department focuses on the implementing modeling and data processing and analysis methods that support decision-making by using approaches derived from mathematics, IT, and physics. The work conducted by the department is applied in nature, as it is based on concrete problems from its areas of expertise—agronomy, agri-food, molecular biology, genetics, ecology, and the environment. These applications enable the MMIP department not only to respond to the challenges addressed by AgroParisTech, but also to identify original research topics that can lead to the development of new methods. Most methods developed in the department are “data-centered,” in that they are guided by data and seek to learn from it, including by deriving suitable models from it.

Collaborations with other laboratories within our subject areas: 

In mathematics and IT: LMO, LRI, CMAP, Maiage, L2S, LIP6, etc.
In applied fields: LSCE, IJPB, GQE, IPS2, Curie Institute.
In engineering physics: FRISE, GEPEA, LGPM, UMET, OPAALE, CEN, etc. 

Industrial partners: SEB, Danone, Orange-Labs, EDF R&D, CEA, Sanofi, L’Oréal, Air Liquide, Bonduelle, Cargill

The MMIP department is responsible for classes in all 3 years of the Engineering program as well as in Master’s programs. It coordinates one major and participates in several different Master’s programs. Classes taught include: 

• Training in math, computer science, and physics skills and methods in which all future engineers must be proficient: core curriculum  
• Specialized training for students seeking more advanced training, through: 
  • Elective teaching units in Years 1, 2, and 3 
  • The IODAA (Leveraging Learning and Analysis for Information and Decision-Making) major available in the third year 
    • Participation in majors organized by other departments: PIST, EDEN, EGE, GIPE, CDP, GPP, etc. 
    • Master’s TUs: AEPTF, AAE, MathSV, BEE, NUTRI, GPB, the AMI2B (Analysis, Modeling, and Engineering for Biological and Medical IT) program within the Bioinformatics Master’s degree, NSA, Process and Bioprocess Engineering, the FIPDes (Food Innovation and Product Design) Erasmus Mundus Joint Master’s Degree and European Master’s Degree in Food Studies, etc.

• UFR Mathématiques appliquées - AgroParisTech
• UFR Sciences physiques pour l’ingénieur - AgroParisTech
• UFR Informatique – AgroParisTech

Research activities at the MMIP department mostly fall within the field of data science, since one of its aims is developing methods for extracting knowledge from data using approaches that stem from applied mathematics (including statistics, i.e. probabilistic and stochastic frameworks), from computer science (i.e. algorithmic and heuristic frameworks), and from physics (i.e. deterministic and mechanistic frameworks). It should also be noted that the MMIP department develops AI-driven methods. Several members of the MMIP department teach statistical and artificial learning methods, a subfield of AI and data science. The department also conducts research into modeling phenomena encountered in the fields of food process engineering and consumer behavior.