Webinar

SciML: Scientific Computing + Machine Learning = Industrial Modeling for Engineers

Webinar

SciML: Scientific Computing + Machine Learning = Industrial Modeling for Engineers

Event Date & Time

May 9, 2023, 12:00 AM

May 9, 2023, 12:00 AM

ET

Speakers

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Event Date & Time

May 9, 2023, 12:00 AM

ET

Speakers

Share

SciML is the mixture of physical modeling and machine learning. In this webinar, Dr. Chris Rackauckas, Lead Developer of the SciML Open Source Software Organization and VP of Modeling and Simulation at JuliaHub, will discuss how utilizing the structured scientific (differential equation) models together with the unstructured data-driven models of machine learning, can accelerate simulators and help simulators approximate the true systems, all while enjoying the robustness and explainability of mechanistic dynamical models. Learn about the impact of SciML on industrial engineering, the benefits of a SciML approach to modeling, and the difference between SciML and other machine learning techniques.

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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SciML: Scientific Computing + Machine Learning = Industrial Modeling for Engineers

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SciML: Scientific Computing + Machine Learning = Industrial Modeling for Engineers