The 7th International Workshop on Symbolic-Numeric Methods for Reasoning about CPS and IoT

Important Dates

Submission Deadline: June 15, 2021

Extended Deadline: July 8, 2021

Firmed Extended Deadline: July 15, 2021

Acceptance Notification: July 28, 2021

Camera-Ready Version: August 15, 2021

Workshop: August 23, 2021

Submission Information

The workshop solicits

  • long research papers (not exceeding 15 pages excluding references),

  • short research papers (not exceeding 6 pages excluding references) and

  • work-in-progress papers (not exceeding 6 pages excluding references).

Research papers must present original unpublished work which is not submitted elsewhere. In order to foster the exchange of ideas, we also encourage work-in-progress papers, which present recent or on-going work.

The papers should be written in English and formatted according to the EPTCS guidelines.

Papers can be submitted using the EasyChair system.

All submissions will undergo a peer-reviewing process.

Accepted research papers will be presented at the workshop and are expected to be published in the Electronic Proceedings in Theoretical Computer Science (EPTCS).

Accepted work-in-progress papers will be presented at the workshop but will not be included in the proceedings.

Topics of Interest

  • Verification, parameter identification and control synthesis for hybrid systems

  • Probabilistic inference and reachability for stochastic hybrid systems

  • Symbolic and numerical integration and decision techniques

  • Emerging applications to safe autonomous systems in uncertain environments

  • Resiliency and dependability in CPS and IoT

  • Temporal logic-based monitoring, reasoning and synthesis for CPS and IoT

We encourage submissions of papers in the following two specific areas:

  • Verification of models used in machine learning and autonomous CPS
    Learning algorithms are at the core of many engineering applications including robotics and autonomous vehicles. We invite research papers on verification of models used in machine learning and autonomous CPS. In particular, recent advances in autonomous cars require addressing challenging questions around their safety and reliability.

  • Symbolic and numerical techniques for verification and synthesis of stochastic models
    Autonomous systems operate in uncertain environments. Thus, it is essential to reason about the effect of uncertainty. We invite research papers on symbolic and numerical techniques for formal synthesis of stochastic systems.