{"id":14767,"date":"2026-08-20T12:53:40","date_gmt":"2026-08-20T12:53:40","guid":{"rendered":"https:\/\/incose.nl\/?page_id=14767"},"modified":"2026-08-24T07:40:07","modified_gmt":"2026-08-24T07:40:07","slug":"stephan-van-beek-mathworks","status":"publish","type":"page","link":"https:\/\/incose.nl\/en\/the-dutch-systems-engineering-days-2026\/stephan-van-beek-mathworks\/","title":{"rendered":"Stephan van Beek"},"content":{"rendered":"
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Stephan van Beek<\/h2>\n<\/div><\/div>

Mathworks<\/p>\n<\/div><\/div><\/div><\/div>

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Bio.<\/strong><\/p>\n

Stephan van Beek<\/span><\/span>\u00a0is a\u00a0<\/span><\/span>Senior Principal Application Engineer<\/span><\/span>\u00a0at\u00a0<\/span><\/span>MathWorks\u00a0<\/span><\/span>with over 18 years of experience supporting aerospace, defense, automotive, semiconductor, and industrial customers across EMEA. He specializes in FPGA\/SoC development, Model-Based Systems Engineering, digital engineering, and AI-enabled workflows. Stephan helps organizations transform engineering processes through simulation, automation, digital threads, and agentic AI, enabling teams to develop increasingly complex systems with greater speed, quality, and traceability.<\/span><\/span>\u00a0<\/span><\/p>\n<\/div><\/div>

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Future-Ready\u00a0Defense\u00a0Engineering:\u00a0<\/span>From Digital Threads to Mission-Level Prediction<\/h4>\n<\/div><\/div>
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Abstract.<\/strong><\/p>\n

As defense systems become increasingly autonomous, software-defined, and multidisciplinary, engineering organizations must move beyond static architectures and descriptive models toward predictive, simulation-driven digital engineering. Future-ready Defense engineering requires executable system models that connect requirements, architecture, design, verification, and operations, enabling engineers to evaluate mission outcomes, system performance, and trade-offs before deployment. This session demonstrates how simulation-driven digital threads support more agile development, faster decision-making, and reduced integration risk across the defense lifecycle.\u00a0\u00a0 Two Defense-focused autonomous systems illustrate this approach. An Autonomous Underwater Vehicle (AUV)<\/span>\u00a0example\u00a0demonstrates\u00a0how mission planning, vehicle dynamics, sensing, control, propulsion, energy management, autonomy, and environmental interactions can be evaluated together within a unified\u00a0system\u00a0simulation. Engineers can assess mission success,\u00a0identify\u00a0failure modes, visualize complex\u00a0behaviors, and explore design alternatives early in development.\u00a0\u00a0 A second example, based on an\u00a0Autonomous Ground Vehicle (AGV)<\/span>\u00a0validation framework, shows how requirements, architecture models, environmental conditions, hardware and software variants, and executable tests can be integrated into a cohesive digital thread. This enables rapid trade-space exploration, scalable verification across thousands of scenarios, and continuous evaluation of mission effectiveness while\u00a0maintaining\u00a0end-to-end traceability.\u00a0\u00a0 Together, these examples highlight how system-level simulation, lifecycle model reuse, integrated verification, automation, and standards-based interoperability help\u00a0defense\u00a0organizations develop and\u00a0validate\u00a0increasingly complex autonomous systems with greater confidence, speed, and mission readiness.<\/p>\n<\/div><\/div>

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Agentic Engineering Workflows for Systems Engineering and FPGA\/SoC development <\/h4>\n<\/div><\/div>

Abstract.<\/strong><\/p>\n

Agentic AI is transforming Model-Based Systems Engineering (MBSE) by enabling intelligent automation of complex engineering workflows while\u00a0maintaining\u00a0the rigor, traceability, and governance\u00a0required\u00a0for modern system development. By combining AI agents with MathWorks System Composer, engineers can accelerate the creation, analysis, and refinement of system architectures while\u00a0maintaining\u00a0full engineering oversight.
\nKey capabilities include:
\n\u2022 Automated requirements analysis and decomposition
\n\u2022 Generation and refinement of system architectures
\n\u2022 Traceability management between requirements, architecture, and implementation
\n\u2022 Model consistency checking and validation
\n\u2022 Orchestration of multi-step engineering workflows spanning system, software, FPGA, and SoC development
\nAgentic workflows combine large language models with engineering tools, planning capabilities, memory, and feedback loops to automate repetitive tasks and support design exploration.\u00a0Rather than replacing engineers, these workflows augment engineering teams by reducing manual effort and allowing them to focus on higher-value design decisions.
\nThis presentation\u00a0demonstrates\u00a0how System Composer provides the structured architectural foundation needed to guide AI-driven workflows and produce transparent, reviewable engineering artifacts. It further shows how architectural intent can be connected to downstream software, FPGA, and SoC implementation workflows, enabling an end-to-end digital thread from requirements through deployment.
\nAttendees will learn\u00a0by means of\u00a0practical use-cases\u00a0how Agentic AI can help to:
\n\u2022 Scale digital engineering practices across multidisciplinary teams
\n\u2022 Improve productivity through intelligent workflow automation
\n\u2022 Accelerate development from requirements and architecture to software, FPGA, and SoC implementation and verification
\n\u2022 Enhance traceability and consistency across the entire system lifecycle<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>

<\/div><\/div><\/div><\/div><\/div><\/section>\n","protected":false},"excerpt":{"rendered":"Stephan van Beek Mathworks Bio. Stephan van Beek\u00a0is a\u00a0Senior Principal Application Engineer\u00a0at\u00a0MathWorks\u00a0with over 18 years of experience supporting aerospace, defense, automotive, semiconductor, and industrial customers across EMEA. He specializes in FPGA\/SoC development, Model-Based Systems Engineering, digital engineering, and AI-enabled workflows. Stephan helps organizations transform engineering processes through simulation, automation, digital threads, and agentic AI, enabling...","protected":false},"author":402,"featured_media":0,"parent":13872,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-14767","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/pages\/14767","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/users\/402"}],"replies":[{"embeddable":true,"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/comments?post=14767"}],"version-history":[{"count":10,"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/pages\/14767\/revisions"}],"predecessor-version":[{"id":14814,"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/pages\/14767\/revisions\/14814"}],"up":[{"embeddable":true,"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/pages\/13872"}],"wp:attachment":[{"href":"https:\/\/incose.nl\/en\/wp-json\/wp\/v2\/media?parent=14767"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}