Industry Expert Talk: From Signals to Systems: Making AI Industrial-Grade Across the Engineering Lifecycle
The rapid adoption of artificial intelligence (AI) has transformed many research areas in signal processing, yet deploying AI reliably at scale across real industrial engineering lifecycles remains a significant challenge. Industrial environments impose constraints that go far beyond benchmark performance: data scarcity and imbalance, data quality, heterogeneity of data sources, non-stationarity, strict reliability and safety requirements, explainability, latency, and long operational lifetimes. This talk explores how signal processing principles, combined with modern AI and emerging computational paradigms, provide a rigorous foundation for making AI truly industrial grade.
We present a lifecycle-centric view of engineering problems—from design and simulation, to manufacturing, deployment, operations and maintenance—and discuss some of the challenges that arise at each stage. Topics include representation learning for unstructured multimodal data, physics-informed and hybrid model-based/data-driven approaches, robust and adaptive learning under distribution shifts, and uncertainty quantification for decision-critical systems. Emphasis is placed on how classical signal processing concepts such as filtering, spectral analysis, system identification, and optimization continue to play a central role in addressing these challenges when integrated with AI.
Beyond AI, the talk also highlights the growing role of alternative computational approaches, including quantum-inspired algorithms and advanced optimization techniques, for tackling large-scale, combinatorial industrial problems. Beyond individual algorithms, the talk will emphasize system-level considerations for deploying signal-driven AI on an industrial scale.
By drawing on Siemens’ global research and real-world industrial examples from manufacturing, engineering design and simulation software, process industries and more, this presentation aims to bridge signal processing, AI and industrial domains. This talk aims to provide the signal processing community with insights into what it takes to move AI from prototypes to mission-critical industrial systems. The talk will conclude by outlining open research challenges and opportunities at the intersection of signal processing, AI, and cyber-physical systems in engineering—areas where the signal processing community can play a decisive role in shaping the next generation of industrial intelligence.
