
Year 2 Research Project
Digital Twin and Machine-Learning Enabled Models for Complex Food Manufacturing and Nutrient Delivery During Digestion
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Description
SIGNIFICANCE
The significance of this proposed research is to address a long-standing unmet need in precision nutrition and additive manufacturing of foods. Specifically, this research will develop AI-enabled predictive models for 3D printed foods and a gut digestion process.
GOALS
The specific goals of this proposal are to develop AI-enabled models for additive manufacturing of food for precision nutrition and AI-enabled digital twin of a gut digestion process to predict and optimize the bioaccessibility of micronutrients during digestion based on diverse composition and structure of foods.
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Team

Nitin Nitin
Principal Investigator

Tarek Zohdi
Principal Investigator

Xin Liu
Co Principal Investigator

Tarek Zohdi
Co Principal Investigator

Qing Zhao
Co Principal Investigator

Khalid Mosalam
Co Principal Investigator

Francesco Borrelli
Co Principal Investigator

Simo Mäkiharju
Collaborator

Mark Mueller
Collaborator

Nitin Nitin
Collaborator
