6th Workshop on Design Automation for CPS and IoT (DESTION 2024)

DESTION 2024 will take place on May 13, 2024 as part of the CPS-IoT Week events.

The target audience of DESTION 2024 is researchers and practitioners of Cyber Physical Systems (CPS) design methodologies, machine learning, experts from the tool industry, and end-users from systems companies engaged in CPS and Internet of Things (IoT) development. Over the last few years, there has been transformative progress in AI/ML methods such as learning accurate surrogate models, generative AI, efficient design space exploration, testing and verification, and formal synthesis. This progress coupled with the rapidly growing scale and complexity of CPS and IoT has fueled immense interest in the development of design automation tools. The primary emphasis of the Workshop is on discussing and demonstrating new design tool concepts, methodologies, implementations, and case-studies for design, verification and testing of CPS and IoT.

Overview

Cyber-Physical Systems (CPS) such as aircraft, automobiles, industrial robots, medical devices, and Internet-of-Things (IoT) applications, promise significant economic and societal benefits. The design, verification, validation, testing, and operation of such systems present several challenges induced by scale, complexity, uncertainty, and many stringent requirements on safety, performance, security, availability, and many other metrics.

There has been a drastic shift in the manner in which products are designed in the past few decades, from being predominantly mechanical and having independent components to being cyber-physical with highly interacting components. This has resulted in an explosion in the design complexity, leading to very long design cycle times. For several of the complex systems presented above the design process can last years involving several redesign loops. To circumvent this issue, the current state of practice relies on "hot-starting" a new design from a known baseline, which unfortunately limits innovation, preventing a detailed exploration of the design space. The design space, on the other hand, is significantly more complex given the interdependent nature of the multidisciplinary design problem. There have been numerous advances in the area of AI for Design Automation methods that have been shown to help in the design of these complex systems, as well as in their autonomous operations. These methods range from natural language processing for requirements engineering, physics-informed models to accelerate simulations, Bayesian methods for uncertainty quantification, probabilistic programming methods to represent designs as a handful of examples. On the other hand, as AI is integrated into a diverse variety of systems such as autonomous vehicles, energy grids, health care, IoTs, and social network platforms, the challenge of design and verification of AI-enabled systems has become extremely important. This has led to new Design Automation for AI methods of interest including network architecture exploration techniques, AI testing and verification methods, simulation tools, ontology-driven design automation, large-language models, heterogeneous simulation integration tools, and neuro-symbolic learning.
 

About DESTION

DESTION provides a premier forum for researchers and engineers from academia, industry, and government to present and discuss challenges, promising solutions, and applications in design automation for CPS and IoT. DESTION 2024 has a broad scope covering techniques and tools for modeling, simulation, synthesis, validation, and verification of CPS and IoT, with a focus on "AI for Design Automation" and "Design Automation for AI", and their applications in a variety of domains, such as automotive and transportation systems, avionics, robotics, building architectures, grid, and medical devices.

We invite contributions in the following main topics (but not limited to):

  • Machine learning in CPS/IoT
  • Assurance and formal verification methodologies
  • Correct-by-construction design and evolution
  • Requirement engineering
  • Real-time execution
  • Test and evaluation
  • Languages and tools for specification and design
  • Architectural design
  • Circuit design
  • Run-time monitoring
  • Benchmarks and datasets
  • Modeling and simulation of CPS
  • Design-space exploration
  • Natural language processing
  • Uncertainty quantification
  • Neuro-symbolic learning

 

Submissions:

 

 

All submissions must be in English. Only original papers that have not been submitted or published in other conferences or journals will be considered. All accepted papers and demo abstracts will be published in IEEE Xplore as part of the DESTION 2024 proceedings.

 

 

Full Papers: Full technical contributions should have no more than 6 pages, excluding references and appendix.

 

 

Shorter Papers, Tool Papers, Benchmark Releases, and Demos: We also welcome shorter papers, tool papers, benchmark releases, and demos via submission of 2-page abstracts, excluding references and appendix. Supplementary materials for tools and demos such as videos, repository links, and online accessible web-applications are encouraged.

 

 

Submission guidelines:

 

 

Please submit your papers and abstracts at https://easychair.org/conferences/?conf=destion2024. The submission can use the ACM Latex template available at https://www.acm.org/publications/proceedings-template.

 

 

 

Important Dates:

 

 

  • 01 March 2024 (AoE): Submission deadline

     

     

  • 08 March 2024: Author notification

     

     

  • 22 March 2024: Camera-ready submission deadline

     

     

 

Previous year’s conference information is available at:

General Chairs:
Himanshu Neema (Vanderbilt University, USA)
Karthik Ramani (Purdue University, USA)
Abhishek Dubey (Vanderbilt University, USA)

Program Co-Chairs:
Arun Ramamurthy (Siemens, USA)

Program Committee:
Himanshu Neema (Vanderbilt University, USA)
Karthik Ramani (Purdue University, USA)
Abhishek Dubey (Vanderbilt University, USA)
Susmit Jha (SRI International, USA)
Alessio Lomuscio (Imperial College London)
Maggie Wigness (Army Research Laboratory)
Sanjai Narain (Perspecta Labs)
Martin Schoeberl (Technical University)
Sydney Whittington (Southwest Research Institute)
Rakesh Kumar (SRI International)
Oleg Sokolsky (University of Pennsylvania)
Christopher McComb (Carnegie Mellon University)
Chuchu Fan (MIT)
Theodore Bapty (Vanderbilt University)
Daniel Balasubramanian (Vanderbilt University)
Paulo Tabuada (UCLA)
Rolf Drechsle (University of Bremen)
Qinru Qiu (Syracuse University)
Pierluigi Nuzzo (University of Southern California)
Aron Laszka (University of Houston)
Wolfgang Reifreif (University of Augsburg)
Prashant Shenoy (University of Massachusetts, Amherst)
Alessandro Pinto (Raytheon Technologies)

Steering Committee:
Janos Sztipanovits (Vanderbilt University, USA)
Qi Zhu (Northwestern University, USA)
S. Shankar Sastry (University of California, Berkeley, USA)
Alberto Sangiovanni-Vincentelli (University of California, Berkeley, USA)
Werner Damm (Carl von Ossietzky Universitat Oldenburg, Germany)
Edward A. Lee (University of California, Berkeley, USA)
Richard Murray (California Institute of Technology, USA)
George J. Pappas (University of Pennsylvania, USA)