AI and Digital Twins with Model-Based Design
Overview
Please join MathWorks at this upcoming in person event to gain technical insights into the development and deployment of digital twins using MATLAB and Simulink. The event will cover key workflows, such as modeling and simulation multi-domain systems, conducting design studies, and building AI algorithms for anomaly detection and predictive maintenance. You will benefit from live demonstrations, practical examples, and direct interaction with MathWorks engineers.
Highlights
- Learn how to build and simulate models using Simulink and Model-Based Design, enabling early validation of complex systems before hardware testing
- Discover techniques for generating synthetic data from digital twin models and training predictive maintenance algorithms to monitor asset health and detect anomalies in real time
- Explore methods for integrating machine learning and deep learning into digital twin models to speed up design iterations, improve system performance, and cut costs
Who Should Attend
This event is designed for engineers and technical professionals seeking to deepen their understanding of applying Model-Based Design and integrating AI into digital twin applications. This event will equip you with the technical skills and best practices needed to implement digital twins for your engineering challenges.
About the Presenter
Karanjodh Singh Meen has a MS in Mechanical Engineering from Arizona State University and BE form Punjab Engineering College, India. He specializes in the areas of control systems, system dynamics and robotics. In 2018, he joined Technical Support at MathWorks and later moved to the Application Engineering Group in 2019. He works with customers in automotive, medical device, industrial automation and aerospace industries specifically supporting workflows that involve modeling physical systems, designing controls, and automatic code generation.
Tianyi Zhu is a product manager at MathWorks focused on Simulink® and AI. He helps engineers worldwide adopt Model-Based Design, integrate AI functionality into embedded systems, and leverage the power of modeling and automation to accelerate development processes. Tianyi holds an M.S. in Engineering Management and M.S. and B.S. degrees in Electrical and Computer Engineering, all from Carnegie Mellon University.
Agenda
| Time | Title |
8:30 |
Registration and Breakfast |
9:00 |
Welcome and Introduction |
9:15 |
Building Digital Twins for System Design
|
10:00 |
Break |
10:15 |
Using Digital Twins for System Operations
|
11:00 |
Break |
11:15 |
Integrating AI into Digital Twin Workflows
|
12:00 |
Lunch |
