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.
Jim Tung is a MathWorks Fellow, focusing on business and technology strategy and working with key customers and partners. Jim has more than 35 years of experience in real-time systems, data acquisition, and technical computing, including 30 years at MathWorks. Jim was previously vice president of marketing and vice president of business development at MathWorks, and earlier held marketing and sales management positions at Lotus Development and Keithley DAS, a pioneering manufacturer of PC-based data acquisition systems.
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.
Mohamed Anas is the Engineering Group Manager, MathWorks Benelux and Switzerland. He leads the customer-facing engineering teams and has expertise in technical computing and design automation. Mohamed has over 20 years of experience applying advanced computing and development processes in the automotive, aerospace, defense, finance and industrial automation and machineries industries. Prior to joining MathWorks in 2005, Mohamed worked at Motorola, Freescale Semiconductor, and BMW, where he held senior positions in the areas of CPU design and verification, multi-domain modelling, and code generation, targeting resource constrained embedded systems. Mohamed received the IET (UK), IEEE, EPSRC, and BMW international research awards in 1998, 1999, and 2000, respectively. He holds an engineering doctorate in Systems-on-Chip design.
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:
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.
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