9:30 - 10:00

Organizations with digital transformation initiatives are making the shift from visionary ambitions to practical projects. These organizations have defined their high-level digital transformation objectives, and are now looking to their engineers and scientists to achieve them. This will involve learning new technologies, collaborating with unfamiliar groups, and proposing new products and services. To meet this challenge, technical organizations must master how to systematically use data and models, not only during the research and development stages, but also across groups throughout the lifecycle of the offering. An effective digital transformation plan needs to consider changes in people’s skills, processes, and technology. Join us as Jim Tung describes this pragmatic approach to digital transformation and demonstrates how engineering and scientific teams are leveraging data and models to achieve their digital transformation objectives.

11:00 - 11:45

Learn about new capabilities in the MATLAB® and Simulink® product families to support your research, design, and development workflows. This talk highlights features for deep learning, wireless communications, automated driving, and other application areas. You will see new tools for preprocessing and analyzing data; developing motor control algorithms; creating interactive apps; packaging and sharing simulations; and modeling, simulating, and verifying designs.

12:15 - 13:30

As part of the Women in Tech initiative, MathWorks will be hosting a Women in Tech lunch during this year’s MATLAB EXPO Benelux, intended for female delegates and presenters. Join the lunch to hear from leading technical experts and to discuss your experiences, and use this opportunity to meet and network with other female industry peers.

14:00 - 14:30

While many organizations get excited about adopting machine learning techniques, success does not come easy. Come to this talk to learn about applications where machine learning generates considerable ROI, including fleet data analysis, energy forecasting, and smart manufacturing. We will also demonstrate how engineers are integrating machine learning techniques with their controls and signal processing workflows to improve system performance.

Throughout the presentation we will highlight new features in MATLAB® that accelerate deploying machine learning. This includes applying automation techniques to feature selection, model selection, and hyperparameter optimization (AutoML). We will also cover new ways for integrating machine learning models with production workflows such as updating deployed models and C/C++ code generation. Come to this talk to learn how your peers have applied machine learning, and to get inspiration for how machine learning could be applied to your own work.

16:00 - 16:30

Automated driving spans a wide range of automation levels, from advanced driver assistance systems (ADAS) to fully autonomous driving. As the level of automation increases, the use scenarios become less restricted and the testing requirements increase, making the need for modeling and simulation more critical. In this session, you will learn and how MATLAB® and Simulink® support engineers building automated driving systems with increased levels of automation. You will learn about new features in R2019b and R2020a to:

• Design perception, sensor fusion, planning, and controls subsystems
• Test by simulating driving scenarios and sensor models in photorealistic scenes
• Deploy by generating C/C++ code

13:30 - 15:00

Brushless motors are everywhere. These motors rely on field-oriented control to regulate currents to motor windings. In this session, we will look at some of the challenges and solutions for developing field-oriented control algorithms to achieve the 10-20KHz switching frequency required for efficient and accurate motor operation.

Highlights:

• Approaches for automatically generating fast compact floating-point and fixed-point code from models
• Methods for developing sensorless field-oriented control algorithms
• Approaches for tuning speed and current loop gains
• Techniques to model and parameterize electrical machines for simulation work

15:30 - 17:00

How do you manage your code and models as they grow, become more complex, and require multiple people to work on them simultaneously? This session will introduce some of the software development tools available in MATLAB® and Simulink® to better manage your files, track changes, work collaboratively, and write more robust applications. We will also discuss how to automate testing and deploy your tests to continuous integration (CI) systems to ensure your application always works.

Highlights:

• Managing your code and model dependencies using Projects
• Tracking changes and working collaboratively using source control (Git)
• Writing better, robust, and portable code and models
• Creating tests to prove your applications works as expected
• Leveraging CI systems (such as Jenkins) to automate testing and reporting