Call for papers
Cyber-physical systems, such as intelligent transportation systems, smart grids, and advanced manufacturing solutions are becoming increasingly prevalent. Developing new methods to integrate measured data and different forms of feedback inside the decision-making mechanism is central for a trustworthy system design. There are distinctive challenges that arise in this scenario, such as the existence of different time-scales, the need to guarantee sufficient richness of the collected data, or the effect of suboptimal decisions under uncertainty.
SysDO aims to focus on these challenges by bringing together researchers working in control, optimization, learning, and in particular at the intersection of these topics. Lasting solutions require an interdisciplinary approach, and we therefore welcome both methodological works that propose new theory and algorithms, as well as cutting-edge applications.
Submission Deadlines:
Opening: February 6, 2024
Initial submission deadline:
May 19, 2024 (extended) May 5, 2024
Acceptance notification: July 29, 2024
Finial submission deadline: September 1, 2024
Topics of interest include (but are not limited to):
- Data-driven control (direct and indirect)
- Uncertainty-aware sequential decision making
- Control theory for optimization algorithms
- Online learning for optimization and control
- Systems theory in learning
To prepare an outstanding technical program, the following two submission categories will be accepted:
- Contributed papers, which feature new research results and will be published in the official conference proceedings (to appear in Springer Lecture Notes in Control and Information Sciences Proceedings)
- Extended abstracts, which contain latest research findings or can be used to disseminate results from a recently submitted/accepted journal publication.