Tutorial

Using Dyad Agentic AI to Optimize Your Thanksgiving Turkey

Tutorial

Using Dyad Agentic AI to Optimize Your Thanksgiving Turkey

Date Published

Nov 26, 2025

Nov 26, 2025

Speakers

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Date Published

Nov 26, 2025

Speakers

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In this Thanksgiving-themed experiment, we use Dyad’s Agentic AI to build and simulate a fully discretized thermal model of a turkey in the oven. Starting from basic geometry and heat-transfer assumptions, the AI agent formulates the governing equations, implements the model, runs simulations, and generates temperature-time plots and animations that reveal how heat travels through the bird. The video walks through each step of this modeling and simulation workflow—including sensitivity studies on oven temperature—to show how agentic AI can automate complex system simulation tasks while preserving physical fidelity. It’s a lighthearted but powerful demonstration of Dyad’s ability to turn real-world physics into fast, high-quality models.

Speakers

Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

Speakers

Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

Speakers

Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

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Want to get enterprise support, schedule a demo, or learn about how we can help build a custom solution? We are here to help.

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Using Dyad Agentic AI to Optimize Your Thanksgiving Turkey

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Using Dyad Agentic AI to Optimize Your Thanksgiving Turkey