Kamal Kansou

Kamal Kansou

 Research fellow

Email : kamal.kansou[a]inrae.fr
Phone : (33) 2 40 67 51 49
https://cv.hal.science/kamal-kansou?langChosen=fr
https://orcid.org/my-orcid?orcid=0000-0002-6262-4447
https://www.researchgate.net/profile/Kamal-Kansou

Actual position and research subject

Research theme : Methods for the assessment of food or bio-based materials in bioeconomy systems

Transformations of plant-based products, either for food or for bio-based materials, must be driven by bioeconomy principles, such as healthier foods, improve re-using, recycling of products. To effectively link these overaching principles to the processing of complex biologicial entities like plant materials (starch, proteins, plant cell wall, wheat flour) is a quite challenging goal, that can benefit from suitable modeling and knowledge engineering method. A part of my research consists in designing and adapting these methods to capture the heterogeneous knowledge about plant-based processing such as technological knowledge about the process conditions – flour specifications and kneading conditions – and the dough sensory properties. To do so I favor knowledge engineering, combing knowledge elicitation and knowledge representation techniques e.g. qualitative reasoning, but also more classical data analysis and modelling techniques.

I am currently researcher at INRAE Nantes. I've got an engineering degree in agronomy and a PhD in process engineering from the University of Science and Technologies of Nantes (France) in 2010. During my PhD my work involved the symbolic representation of know-how associated with breadmaking, and I was a co-author of an expert system about the baking test, called Ascopain. From 2010 to 2011 I was postdoctoral fellow at the Informatics Institute of the University of Amsterdam during which I worked on the use of conceptual modelling based on Qualitative Reasoning to review research works in the field of natural science. My current research involves the development of data-based and knowledge-based models applied to food or agro-product quality and processing.