AI-Driven Synthesis for High-Tech System Design: Automating Innovation

Computer Science > Artificial Intelligence [Submitted on 26 Jun 2026] AI-Driven Synthesis for High-Tech System Design: Automating Innovation Luuk Oerlemans, Steven Westerhof, Theo Hofman This article addresses the combinatorial complexity inherent in modern high-tech system design by presenting automation-in-design (AiD) as a transformative paradigm. We propose computational design synthesis (CDS), a framework utilising deep learning and generative AI to automate the creation of novel systems. Two case studies (e-drive system design and spatial dimensioning problem) serve as proof-points for this approach. The AI-driven methods used in the case studies represent a fundamental shift in engineering, advancing from simulation-based optimisation towards autonomous design with minimal human supervision. Subjects: Artificial Intelligence (cs.AI); Hardware Architecture (cs.AR); Computational Engineering, Finance, and Science (cs.CE); Emerging Technologies (cs.ET); Robotics (cs.RO) Cite as: arXiv:2606.28126 [cs.AI]   (or arXiv:2606.28126v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2606.28126 Focus to learn more Submission history From: Theo Hofman [view email] [v1] Fri, 26 Jun 2026 14:26:48 UTC (17,301 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.AR cs.CE cs.ET cs.RO References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)