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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

Portrait of Nitin Nitin

Nitin Nitin

Principal Investigator

Portrait of Tarek Zohdi

Tarek Zohdi

Principal Investigator

Portrait of Xin Liu

Xin Liu

Co Principal Investigator

Portrait of Tarek Zohdi

Tarek Zohdi

Co Principal Investigator

Portrait of Qing Zhao

Qing Zhao

Co Principal Investigator

Portrait of Khalid Mosalam

Khalid Mosalam

Co Principal Investigator

Portrait of Francesco Borrelli

Francesco Borrelli

Co Principal Investigator

Portrait of Simo Mäkiharju

Simo Mäkiharju

Collaborator

Portrait of Mark Mueller

Mark Mueller

Collaborator

Portrait of Nitin Nitin

Nitin Nitin

Collaborator

Portrait of Ilias Tagkopoulos

Ilias Tagkopoulos

Collaborator