Visible to the public CfP: Workshop on Machine Learning In ControlConflict Detection Enabled

No replies
Anonymous's picture



May 11, 2021 | at CPS WEEK 2021

The venue gathers leading experts to present cutting edge results within the data-driven design of control systems.


Inquiries about the nature and structure of concepts, data- vs. model-based knowledge, have become central in CPS research. It is not surprising that the philosophical rivals, empiricism and rationalism have been battling for many hundred years. Despite advances in machine learning and success stories in social and mass media, learning is still very challenging.

This workshop is a consequence of the transition of the CPS community from the model-based to data-based methods. From the position of having only a few high-quality sensors to the case where data is omnipresent, but often of varying quality. We strive to learn the machines and infrastructures, to work autonomously, work together and collaborate with people.

We need new paradigms for the theory and practice of CPS. This workshop is the first step of joining research forces in formalizing and subsequently solving learning, safety assessment and verification problems.


  • Claire Tomlin (UC Berkeley, USA)
  • Aaron Ames (California Institute of Technology, USA)
  • Michael Fisher (University of Manchester, UK)
  • Akshay Rajhans (MathWorks, USA)
  • Sayan Mitra (University of Illinois, USA)
  • Cristina Seceleanu (Malardalen University, Sweden)
  • Radu Grosu (Vienna University of Technology, Austria)
  • Joost-Pieter Katoen (RWTH Aachen University, Germany)
  • Draguna Vrabie (Pacific Northwest National Laboratory, USA)
  • Maryam Kamgarpour (The University of British Columbia, Canada)


We are inviting you to submit your work in progress on the topics related to the following areas and their applications:

  • Reinforcement learning for CPS
  • Machine learning techniques for CPS
  • Modelling of human behavior and sociotechnical systems
  • Safety verification and computation


Please send up to 4 pages short papers

Submission Deadline: Feb 22, 2021

Submit here