08:30
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Registration and Welcome
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09:00
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Welcome and Introduction
09:00–09:30
Tanya Morton
MathWorks
Hall 3
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Tanya Morton
MathWorks
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Hall 3 |
09:30
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Keynote: Embedded Intelligence: The Future of AI in Engineering Design
Artificial intelligence, especially generative AI, is changing engineering design. It handles routine tasks and helps engineers be more creative in three key ways:
- Accelerating the engineering design loop by providing faster, data-driven solutions.
- Mixing human ideas with AI insights, changing the role of designers.
- Improving engineering design tools, making it easier to turn creative concepts into accurate, ready-to-build solutions.
See how these advancements help engineers move beyond traditional limits and effectively bridge imagination with practical solutions.
Jon Friedman, Senior Manager
MathWorks
Dr. Jon Friedman is a senior manager in Industry Marketing at MathWorks, with 20+ years of experience there. Jon leads a team of industry experts focused on helping leading companies in the AeroDef and auto industries adopt Model-Based Design through the sharing of best practices. He was also part of the team that conceived and launched System Composer, which connected MATLAB and Simulink to model-based system engineering workflows. Jon’s career began with thesis work focused on the application of robust system identification and control theory. He held research and product development positions in the commercial and defense sectors of the automotive and aerospace industries. In addition to experience deploying Model-Based Design and code generation at a Fortune 50 company, he has been a program manager on multiple vehicle programs; led lean engineering and manufacturing projects; and authored over 50 papers and articles on modeling and Model-Based Design. Jon holds an M.B.A. and Ph.D. from the University of Michigan.
09:30–10:00
Jon Friedman, Senior Manager
MathWorks
Hall 3
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Jon Friedman, Senior Manager
MathWorks
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Hall 3 |
10:00
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Keynote: Generating Information Advantage in a Complex Defence Environment
Digital threads provide a link between design artifacts such as models, simulations, requirements, and tests. Creating a digital thread with modular, reusable components within a model-driven engineering process enables enterprises to achieve earlier verification of complex, multidomain, system-of-system designs and move to more cost-effective product line development. Follow the journey of Leonardo Electronics UK in evolving model-driven workflows and the benefits this brings. Topics include:
- Reusable model repositories of assured components
- Digital threads and reference architecture templates
- Digital twin and continued validation of models with fielded products process.
Mike Stephenson, Lead Systems Engineer
Leonardo
Mike Stephenson has worked for Leonardo Electronics for the last 20 years. He is currently vice president of Systems Engineering. In addition to this role, he helps drive Leonardo’s digital capability in emergent markets. Initially starting his career in software engineering for surveillance radars, Mike moved into fire-control radar for the next 10 years, specialising in Modular Open System Architecture, which among many capability points looked at how to mix Simulink with other programming languages. A passion for adaptability, flexibility, and agility persuaded Mike to take on a role in high-tech modelling and simulation, leading a team of 100 modellers. The change afforded him an opportunity to lead a group involved in solving complex science problems, stretching the computational power of Leonardo airbourne platforms for DSP. Just before COVID, Mike became head of Software Engineering, focussing on digital platforms, flow, and DevSecOps. He then moved into his current role.
Marc Willerton, Principal Application Engineer
MathWorks
Marc Willerton is a principal application engineer at MathWorks supporting the European defence industry. Topics of focus include Model-Based Design and implementation workflows for radar, wireless communication, and RF systems. Before joining MathWorks in 2013, Marc carried out research around array signal processing and software-defined radio, sponsored by the University Defence Research Centre in Signal Processing. Marc received his master’s and Ph.D. degrees in electrical and electronic engineering from Imperial College London, UK.
10:00–10:30
Mike Stephenson, Lead Systems Engineer
Leonardo
Marc Willerton, Principal Application Engineer
MathWorks
Hall 3
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Mike Stephenson, Lead Systems Engineer
Leonardo
Marc Willerton, Principal Application Engineer
MathWorks
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Hall 3 |
10:30
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Break
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11:15
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Accelerating Vehicle Controls Development with Cloud-Based MIL Simulation
Virtual development is increasingly central to OEM strategies, especially in the hypercar segment, where production and development costs are substantial. This approach spans from early-stage prototyping to feature and component validation via model-in-the-loop (MIL) and driver-in-the-loop (DIL) methodologies, leveraging high-fidelity digital twin vehicle models correlated with real-world data. McLaren has focused on enhancing its virtual development capabilities, targeting both accurate, parameterized vehicle models and a scalable infrastructure to manage multiple variants (e.g., sport, ultimate, supercars). Emphasis has been placed on the design and integration of high-level control strategies affecting vehicle handling and performance. See a workflow based on MATLAB® and Simulink® that enables functional verification of critical features in a virtual environment, well before physical prototypes become available. The workflow is integrated within the McLaren cloud ecosystem, supporting seamless model and software deployment across engineering teams and facilitating early identification of bugs and integration issues—thus improving quality and reducing time-to-market. A use case is presented involving the active aerodynamics system of the upcoming McLaren W1, where a custom function is validated in the MIL environment using structured release procedures. This ensures system controllability and robustness during virtual testing. Moreover, the simulation environment is DIL-compatible, allowing early tuning and calibration of control algorithms through driver-in-the-loop sessions. This front-loaded approach reduces risk during physical validation and accelerates development timelines.
Guglielmo Luca Bambino
McLaren Automotive
11:15–11:45
Guglielmo Luca Bambino
McLaren Automotive
Hall 3
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Guglielmo Luca Bambino
McLaren Automotive
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Hall 3 |
Accelerated ASPICE Compliance of Embedded Battery Algorithms with MATLAB and Simulink
In the evolving landscape of automotive software development, ASPICE (Automotive SPICE) compliance stands as a reference benchmark for quality and process maturity. As the industry accelerates toward electrification, ensuring the reliability and compliance of embedded battery algorithms becomes increasingly critical. Explore how MATLAB®,, Simulink®, and key products such as Requirements Toolbox™ and Simulink Test™ can be effectively used to accelerate ASPICE compliance in battery algorithm development. By enabling early validation, simulation-driven testing, and traceability across requirements, models, and test cases, these tools support a structured, auditable, and efficient development process.
Yoann Nauel
Fortescue Zero
11:15–11:45
Yoann Nauel
Fortescue Zero
Hall 1
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Yoann Nauel
Fortescue Zero
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Hall 1 |
11:45
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Accelerating Vehicle Development with Virtual Vehicles
The recent trend of vehicle manufacturers bringing feature development in-house to enable differentiating innovations at a managed level of risk has escalated the need for trusted and useful system-level simulations. These “virtual vehicle” models can enable early discovery and solution of technical risks—i.e. to “fail fast” and innovate quickly in simulation, with expensive vehicle testing used selectively to validate findings. They can, though, present challenges in trusting their results, managing their complexity, and efficiently gleaning insight from them.
Discover the challenges and approaches in virtual vehicle–enabled development and how to use MATLAB® and Simulink® to enable and accelerate this process—from component design and development, through integration of components to system-level simulations, toward scaling up these simulations beyond the desktop.
11:45–12:15
Andrew Odhams
MathWorks
Hall 3
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Andrew Odhams
MathWorks
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Hall 3 |
Enhancing Software Quality and Productivity with Cross-Functional Collaboration
To satisfy the steadily increasing amount of software we encounter daily, more advanced solutions are required where scalability and automation are key. Discover how to tackle these challenges using products like System Composer™ to ensure consistency and traceability as your system evolves. Automate CI activities to increase efficiency, reduce manual effort, and catch errors early in the development process. Finally, use a package management solution to streamline dependency management and foster seamless cross-team collaboration within your organization.
Caroline Dahlgren
MathWorks
11:45–12:15
Caroline Dahlgren
MathWorks
Hall 1
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Caroline Dahlgren
MathWorks
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Hall 1 |
12:15
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Lunch
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13:45
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Panel Discussion: Women in Tech: Navigating Career Transitions and Transformations
The Women in Tech session brings together a panel of senior women technical leaders to share their insights and career journeys. Learn from inspirational women as they reflect on the transitions and transformations that have shaped their professional journeys—from role and industry shifts to adapting to emerging technologies.
13:45–14:15
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Hall 3 |
14:15
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What’s New in MATLAB and Simulink in 2025
Hear from engineers from the MathWorks development team, who will introduce new capabilities and features in MATLAB® and Simulink®.
Explore the new MATLAB desktop and the latest features, such as MATLAB Copilot, designed to improve the productivity of engineers across industry and academia. Discover new capabilities in the Simulink product family that aim to increase the efficiency of workflows using Model-Based Design.
Deborah Ferreira
MathWorks
14:15–14:45
Deborah Ferreira
MathWorks
Angel Gonzalez
MathWorks
Hall 3
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Deborah Ferreira
MathWorks
Angel Gonzalez
MathWorks
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Hall 3 |
14:45
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Break
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15:30
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Virtual EPU: Building and Correlating a Digital Twin
15:30–16:00
Nikolaos Apostolopoulos
Evolito
Hall 3
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Nikolaos Apostolopoulos
Evolito
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Hall 3 |
Biomechanical Analysis with BoB
Biomechanics of Bodies (BoB) is a comprehensive human musculoskeletal model, entirely developed in MATLAB®, which can be used for biomechanical analysis. Using advanced features of the MATLAB graphics system and Optimization Toolbox™, BoB provides a realistic dynamic representation of the human body as commanded by the user. BoB can display the kinematics of human movement and calculate numerous biomechanical kinetic metrics including skeletal, joint, and muscle forces; joint torques; and energy/power expenditure within the body. BoB is widely used for many applications including research by universities, engineering design analysis (such as ergonomics and product development), and sporting performance optimisation—making it a versatile tool for both scientific and engineering applications.
James Shippen
BoB Biomechanics
15:30–16:00
James Shippen
BoB Biomechanics
Hall 1
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James Shippen
BoB Biomechanics
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Hall 1 |
16:00
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Scalable Distributed Simulation for Multi-Actor Scenarios
As engineered systems become more complex and interconnected, industries are seeking simulation techniques that can achieve greater scale and fidelity. This challenge can be addressed by distributing the execution of models across multiple computers.
Discover how System Composer™ can be used to architect distributed simulations of scenarios involving many interacting actors. See how each actor—such as an automotive vehicle or aircraft—can operate independently and exchange data with other actors using a publish-subscribe communication network. Learn about the fundamentals of simulation distribution, including actor scheduling and coordination. See practical examples that demonstrate the potential for scalable, multi-actor scenario simulation.
16:00–16:30
Ben Mohankumar
MathWorks
Hall 3
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Ben Mohankumar
MathWorks
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Hall 3 |
Building and Deploying Robust AI in Engineered Systems
AI has demonstrated improved capability over established algorithms across a wide range of applications. This potential has spurred interest in deploying AI models within engineered systems across sectors such as aerospace, automotive, and healthcare.
Productionizing AI models for safety-critical applications poses new challenges for systems integration, verification, and validation. The structure of AI models has incompatibilities with established methods for assessing safety and can cause AI-specific vulnerabilities.
Learn how to use MATLAB® and Simulink® to assess and improve trust in AI models across all stages of design. The robust models and safety monitors produced can enable certification against both existing and upcoming AI-specific safety standards.
16:00–16:30
Lewis Lea
MathWorks
Hall 1
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Lewis Lea
MathWorks
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Hall 1 |
16:30
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End of Event
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