Overview
Simulation has become an integral part of product development in almost all industries, and is reaching new levels with trends like Digital Twins. How can the power of simulation be combined with the impressive models behind the AI hype? Truth be told – in many ways.
In this session we will talk about four large trends for AI and Simulation:
- AI for Reduced Order Modelling (ROM) – a way of managing the computational burden from High-Fidelity models.
- AI based Virtual Sensors – mimicking a physical sensor where real values cannot be measured.
- Reinforcement Learning based Controls – letting the model learn from a simulation environment
- AI model enhancement using Digital Twins – diversify your dataset using simulation.
About the Presenters
Sebastian Bomberg is an application engineer at MathWorks, supporting customers from various industries in implementing artificial intelligence projects. For instance, he develops applications for forecasting, predictive maintenance, IoT and fleet analytics in general. To this end, he uses techniques from machine learning and deep learning as well as big data algorithms and cloud computing. Sebastian Bomberg holds a Dipl.-Ing. degree in mechanical engineering from the Technical University of Munich, where he also worked as a researcher at the Thermo-Fluid Dynamics Group.
Constanze Ruf is an application engineer at MathWorks focusing on the MATLAB product family. She deepens her knowledge in Machine Learning methods during technical requests from customers as well as in customer interactions. Before joining MathWorks, she elaborated different machine learning approaches in supervised and unsupervised learning during her Master's Thesis in the field of driving style recognition and classification for Porsche, supervised by the Technical University of Munich.
