Call for papers

Contribute to MADTECC 2024!

Posted by Lukas Esterle, Sara Montagna, and Danilo Pianini on Monday, June 13, 2022

Recent trends in computer science promoted new ways to think about software at both design time and run time. Next-generation intelligent pervasive systems will be modelled as digital twins that are counterparts of physical objects and executed in parallel. Moreover, combining the mirroring of the physical entities – that allows for continuous observation of the real world and the corresponding update of the digital replica – with computational intelligence enables the individual devices to operate responsibly towards their goals. Specifically, with digital twins, their execution can become cumbersome and resource intensive. However, utilising a dynamic infrastructure, information processing can be enabled on the edge or the centre of the network, depending on the specific application goals and non-functional requirements.

At the same time, medical applications are first in line to benefit from these new possibilities and one of the most challenging scenarios for emerging technologies, as they require extremely low fault probability, very high availability, great ergonomics, and stringent privacy and security mechanisms. In the medical field, they can support both development (building better products) and applications, improving the comfort of the patient and the precision of medical decisions and operations. The intelligence that can be embedded in the digital twin, or added at the application level, may indeed provide a real-time context awareness on top of which elaborate decision support. This is particularly useful for physicians in fast-critical scenarios, for instance, or for patients in home care, such as for the self-management of chronic diseases.

A set of specific issues arises once engineering and developing digital twins in this field. Since e-health relies on fast response, high fidelity and accurate results, engineering and operating with digital twins in a time-critical manner within a safety-critical application requires novel techniques and methodologies. A trade-off between fast response and high fidelity arises, demanding a potential interaction across the edge-cloud continuum, which can support the reliable and efficient execution of modern medical applications.

In MADTECC we call for experts to contribute to the advancements of medical applications of digital twins by providing original manuscripts describing novel research or experience reports. Moreover, we seek specific consideration of and approaches for the edge-cloud compute continuum in medical and e-health applications.

More specifically, topics of interest include, but are not limited to:

  • Digital twins for pervasive medical devices
  • Digital twin engineering for safety-critical applications
  • Embedded decision-making in e-health applications
  • Coordination of digital twins in the edge-cloud continuum for pervasive and medical applications
  • Computational intelligence for the edge-cloud continuum
  • Medical data and applications in the edge-cloud continuum: security and privacy
  • Explainable AI with humans-in-the-loop and pervasive applications
  • Trustworthy embedded AI in cognitive digital twins
  • Autonomous operation and interaction using digital twins
  • Edge-cloud continuum-supported AI systems for healthcare
  • Cognitive digital twins for complex decision making
  • Applications of digital twins to specific healthcare contexts

Submission instructions

Authors are invited to submit full papers that are unpublished and not under review elsewhere.

Paper format

  • Workshop papers are to be no more than 6 pages (overall, i.e. including references)
  • FORMAT: IEEE template, 10 pt, 2-column format (same template as the main conference)
  • All submissions will undergo a peer-review process by Technical Commitee members
  • All accepted papers will be published as part of the PerCom satellite events proceedings. Proceedings will be published by the IEEE and available online through IEEE Digital Library
  • Papers can be submitted via EDAS at link
  • Each accepted workshop paper requires a full PerCom registration (no registration is available for workshops only)