XAIPE 2026 is co-located with the 24th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2026).
The increasing complexity of modern industrial plants, combined with the availability of large volumes of sensor and process data, has opened unprecedented opportunities for the application of Artificial Intelligence in process engineering. At the same time, safety and regulatory requirements impose stringent constraints on the transparency and interpretability of automated decision-support systems deployed in critical environments.
Purely data-driven models may struggle when extrapolating beyond the operating conditions represented in the training data, particularly with noisy measurements, limited fault examples, or evolving process behaviour. Physics-informed and hybrid AI approaches are becoming increasingly important: by embedding first-principles models into learning architectures, these methods offer a route towards more robust, data-efficient, and physically consistent models for process engineering.
Incorporating physical knowledge does not remove the need for explainability. Physics-informed neural networks, hybrid digital twins, and constrained learning systems may still include opaque data-driven components and complex interactions between mechanistic and learned representations. A further dimension of growing importance concerns the resilience and security of industrial control systems and cyber-physical systems, where explainability is often necessary to distinguish physically meaningful deviations from sensor faults or cyber-attacks.
XAIPE provides a dedicated forum at the intersection of artificial intelligence, process engineering, industrial safety, and cyber-physical system security. The workshop welcomes contributions that advance explainable, physics-aware, trustworthy, and deployable AI methods for industrial processes — spanning the chemical industry, pharmaceuticals and biotechnology, food and beverages, energy production and storage, water and waste treatment, metallurgy and advanced materials, and other safety-critical systems.
XAIPE welcomes original contributions on the following topics. The list is not exhaustive.
Note: the camera-ready deadline (September 14) falls after the AIxIA early registration deadline (September 4). Authors of accepted papers are encouraged to register early regardless, as at least one author per accepted paper must register and present at the workshop.
Authors are invited to submit original, unpublished research papers written in English. Papers will be reviewed by at least two members of the Program Committee. Submissions must be formatted according to the CEUR Workshop Proceedings style (single-column format), available on Overleaf.
Papers must be submitted electronically in PDF format via EasyChair.
EasyChair submission link
easychair.org/conferences/?conf=xaipe2026
Accepted papers are intended to be published in the AIxIA Series of CEUR Workshop Proceedings (indexed by DBLP and Scopus), subject to compliance with CEUR-WS publication requirements. At least one author of each accepted paper is expected to register for AIxIA 2026 and present the work at the workshop.
Lelio Campanile, PhD
Assistant Professor (RTD-A)
Dipartimento di Matematica e Fisica
Università degli Studi della Campania Luigi Vanvitelli, Caserta, Italy
Prof. Francesco Di Natale
Full Professor
Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale (DICMaPI)
Università degli Studi di Napoli Federico II, Naples, Italy
XAIPE 2026 is co-located with AIxIA 2026 — the 24th International Conference of the Italian Association for Artificial Intelligence — held in Perugia, Italy, October 6–9, 2026.