Call for Papers
In March 2027, the Symposium on Hybrid Intelligence in Product and Production Engineering will take place for the second time. This year, the symposium will be held in Berlin. During the two-day symposium, the academic discussion will focus on how hybrid decision support can improve performance in product creation.
Key dates for taking part in HIPPE 2027
Abstract submission deadline
August 10 2026
(click here for further information: t3://page?uid=212900#1008173)
Notification to authors (abstract)
September 11 2026
Full paper submission deadline
January 17 2027
(click here for further information: t3://page?uid=212900#1008173)
Notification to authors (full paper)
February 22 2027
Submission of revised papers by authors
March 07 2027
HIPPE 2027
March 16-18 2027
Abstract submission
To participate in the symposium, an abstract in English of no more than 200 words must be submitted via the conference tool by August 10, 2026. Abstracts will be submitted anonymously via the ConfTool conference tool.
Full paper submission
The deadline for submitting full papers corresponding to accepted abstracts is 17 January 2027. The maximum paper length is 10 pages. The formatting template is available for download here: t3://page?uid=212900#1008129
Note: Registration is not considered complete until payment of the conference fee has been received. All participants will receive a confirmation email. Accepted papers will be published in the conference proceedings, “HIPPE Proceedings.” Papers will generally only be published if one of the authors presents them in person at the conference. No changes to the list of authors will be accepted after the paper has been submitted.
Conference Scope
The symposium will explore the full spectrum of product and production engineering. Key topics include AI in technical processes, data-driven product and production engineering, human-centered AI systems, intelligent production technologies, digital engineering methods, autonomous and self-regulating production systems, and decision-support approaches for complex industrial environments.
Engineering Data and Knowledge
Hybrid intelligence combines multimodal engineering data with human knowledge, experience, and heuristic approaches in product and production engineering. This vast amount of data presents challenges that existing technologies cannot overcome. The focus is on integrating data-driven and knowledge-based perspectives to support complex technical decisions.
DS/AI Technologies and Solution Approaches
Symbolic, subsymbolic, and neurosymbolic AI technologies form the foundation for hybrid intelligence in product development. Architectures, agent-based systems, and AI workflows expand the capabilities of data- and knowledge-based systems. This leads to adaptive and scalable solutions for complex decision-making situations.
Human-Centric Approach
At the centre of hybrid intelligence is effective collaboration between humans and AI in development and production environments. Transparent interactions, trustworthy systems and traceable processes are key prerequisites for this. Consequently, human expertise is complemented by hybrid intelligence.
Sustainability and circularity
Hybrid intelligence opens up new possibilities for sustainable and circular product development. Combining human judgement with data-driven methods enables environmental and economic requirements to be considered early on. The return of products to material cycles creates value and enables the transition to a circular economy.
If you have any questions, please email us: info@hippesymposium.org