Webinar Recording
Dyad Live Modeling Challenge: Building a Quadrotor Model with Agentic AI
Webinar Recording
Dyad Live Modeling Challenge: Building a Quadrotor Model with Agentic AI
The Dyad Modeling Live Challenge is a weekly series where real engineering and modeling problems are tackled live using Dyad and its agentic AI capabilities. In this session, the team worked through a hands-on quadrotor modeling and simulation example.
The walkthrough started with a clean 6-DoF academic quadrotor model using a cascaded PID controller for position and attitude control. From there, realism was added step by step, with each modeling choice validated before progressing further.
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.
Contact Us
Want to get enterprise support, schedule a demo, or learn about how we can help build a custom solution? We are here to help.
Contact Us
Want to get enterprise support, schedule a demo, or learn about how we can help build a custom solution? We are here to help.
