[AISWorld] CfP 5th Workshop on Artificial Intelligence and Model-Driven Engineering (MDE Intelligence) at MoDELS 2023

Tue May 16 16:26:05 EDT 2023

5th Workshop on Artificial Intelligence and Model-Driven Engineering 
(MDE Intelligence 2023)

October 1-6, 2023. Västerås, Sweden

https://mde-intelligence.github.io/

-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-

-=-=-=-=-=-=-=-
THEME & GOALS
-=-=-=-=-=-=-=-

Artificial Intelligence (AI) has become part of everyone's life. It is 
used by companies to exploit the information they collect to improve the 
products and/or services they offer and, wanted or unwanted, it is 
present in almost every device around us. Lately, AI is also impacting 
all aspects of the system and software development lifecycle, from their 
upfront specification to their design, testing, deployment and 
maintenance, with the main goal of helping engineers produce systems and 
software faster and with better quality while being able to handle ever 
more complex systems and software.

There is no doubt that MDE has been a means to tame until now part of 
this complexity. However, its adoption by industry still relies on their 
capacity to manage the underlying methodological changes including among 
other things the adoption of new tools. To go one step further, we 
believe there is a clear need for AI-empowered MDE, which will push the 
limits of "classic" MDE and provide the right techniques to develop the 
next generation of highly complex model-based system and software 
systems engineers will have to design tomorrow.

This workshop provides a forum to discuss, study and explore the 
opportunities and challenges raised by the integration of AI and MDE.

We would like to address topics such as how to choose, evaluate and 
adapt AI techniques to Model-Driven Engineering as a way to improve 
current system and software modeling and generation processes in order 
to increase the benefits and reduce the costs of adopting MDE. We 
believe that AI artifacts will empower the MDE tools and boost hence the 
advantages, and then adoption, of MDE at industry level.

At the same time, AI is software (and complex software, in fact), we 
also believe that such AI-powered MDE approach will also benefit the 
design of AI artifacts themselves and specially to face the challenge of 
designing "trustable" AI software.

Last but not least, although AI is the most popular branch of computer 
science to create and simulate intelligence, we also believe that any 
kind of technique that provides human cognitive capabilities and helps 
creating "intelligent" software are also in the scope of this workshop. 
An example would be the knowledge representation techniques and 
ontologies that can be useful on its own or support other kinds of AI 
techniques.

-=-=-=-=-=-=-=-=-=-
TOPICS OF INTEREST
-=-=-=-=-=-=-=-=-=-

Model-driven engineering (MDE) and artificial intelligence (AI) are two 
separate fields in computer science, which can clearly benefit from 
cross-pollination and collaboration. There are at least two ways in 
which such integration—which we call MDE Intelligence—can manifest:

* Artificial Intelligence for MDE. MDE can benefit from integrating AI 
concepts and ideas to increase its power: flexibility, user experience, 
quality, etc. For example, using model transformations through 
search-based approaches, or by increasing the ability to abstract from 
partially formed, manual sketches into fully-shaped and formally 
specified meta-models and editors.

* MDE for Artificial Intelligence. AI is software, and as such, it can 
benefit from integrating concepts and ideas from MDE that have been 
proven to improve software development. For example, using 
domain-specific languages allows domain experts to directly express and 
manipulate their problems while providing an auditable conversion 
pipeline. Together this can improve trust in and safety of AI 
technologies. Similarly, MDE technologies can contribute to the goal of 
fair and explainable AI.

Topics of interest for the workshop include, but are not limited to:

AI for MDE
=-=-=-=-=-=-
* Application of (meta-heuristic) search and machine learning to 
modelling problems;
* Machine learning of (meta-)models, concrete syntax, model 
transformations, etc.;
* AI planning applied to (meta-)modelling, and model management;
* AI-supported modelling (e.g., bots, recommenders, UI adaptation, etc.)
* Model inferencers and automatic, dataset-based model generators;
* Self-adapting code generators;
* Semantic reasoning, knowledge graphs or domain-specific ontologies;
* AI-supported model-based digital twins;
* Probabilistic, descriptive or predictive models;
* AI techniques for data, process and model mining and categorisation;
* Natural language processing applied to modelling, including Large 
Language Models (LLM) and Generative AI;
* Data quality and privacy issues in AI for MDE;
* Reinforcement learning to optimize modelling tasks.

MDE for AI
=-=-=-=-=-=-
* Domain-specific modelling approaches for AI planning, machine 
learning, agent-based modelling, etc.;
* Model-driven processes for AI system development;
* MDE techniques for explainable and fair AI;
* Using models for knowledge representation;
* Code-generation for AI libraries and platforms;
* Architectural languages for AI-enhanced systems;
* MDE for federated learning;
* Model-based testing/analysis of AI components.

General
=-=-=-=-
* AI in teaching MDE;
* Tools, frameworks, modeling standards;
* Experience reports, case studies, and empirical studies;
* Challenges.

=-=-=-=-=-=-
SUBMISSIONS
=-=-=-=-=-=-

Submissions must adhere to the IEEE formatting instructions, which can 
be found here. We ask for two type of contributions:

1) Research papers: 8 pages,
2) Vision papers, experience papers or demos: 5 pages.

Submissions must be uploaded through EasyChair in the following link 
https://easychair.org/conferences/?conf=mdeintelligence2023.

All submissions will follow a single-blind review process where each 
paper will be reviewed by at least 3 members of the program committee. 
They will value the relevance and interest for discussions that will 
take place at the workshop. Accepted papers will be published in the 
joint workshop proceedings published by the IEEE.

Papers submitted to MDE Intelligence 2023 must not be under review or 
submitted for review elsewhere whilst under consideration for MDE 
intelligence 2023. Contravention of this concurrent submission policy 
(as stated explicity by the IEEE on 
https://www.comsoc.org/publications/ieee-communications-society-policy-plagiarism-and-multiple-submissions) 
will be deemed as a serious breach of scientific ethics, and appropriate 
action will be taken in all such cases.

=-=-=-=-=-=-=-=-=
IMPORTANT DATES
=-=-=-=-=-=-=-=-=

Paper submission: July 17, 2023
Notification: August 15, 2023
Camera-ready: August 22, 2023
Workshop: October 1-3, 2023

=-=-=-=-=-=-=-=-=-=
PROGRAM COMMITTEE
=-=-=-=-=-=-=-=-=-=

Shaukat Ali (Simula Research Laboratory, Norway)
Robert Clarisó (Universitat Oberta de Catalunya, Spain)
Istvan David (Université de Montréal, Canada)
Mattia Fumagalli (University of Bolzano, Italy)
Antonio Garmendia (Universidad Autónoma de Madrid, Spain)
Sébastien Gérard (CEA List, France)
Kamal Karlapalem (IIIT Hyderabad, India)
Wolfgang Maass (DFKI, Saarland University, Germany)
Phuong Nnguyen (University of L'Aquila, Italy)
Bentley Oakes (Université de Montréal, Canada)
Aurora Ramírez (University of Córdoba, Spain)
Davide di Ruscio (University of L'Aquila, Italy)
Rijul Saini (McGill University, Canada)
Daniel Strüber (Radboud University Nijmegen, Netherlands)
Gabriele Taentzer (Philipps-Universität Marburg, Germany)
Marina Tropmann-Frick (Hamburg University of Applied Sciences, Germany)
Steffen Zschaler (King’s College London, UK)

-=-=-=-=-=-
Contact
-=-=-=-=-=-

For additional information, clarification, or answers to questions, 
please contact the Organizing Committee by email at 
mdeintelligence2023 at easychair.org 
<mailto:mdeintelligence2021 at easychair.org>

-- 
Ass. Prof. Dr. Dominik Bork
Assistant Professor for Business Systems Engineering
Business Informatics Group (BIG)
Institute of Information Systems Engineering
TU Wien
Favoritenstr. 9-11 / 194-3

Web:https://model-engineering.info/

Recent Research Highlights:
* Systematic Mapping Study on Conceptual Modeling and AI
https://doi.org/10.48550/arXiv.2303.06758
* AI-enhanced Hybrid Decision Management
https://doi.org/10.1007/s12599-023-00790-2
* UML Modeling in VS Code
https://marketplace.visualstudio.com/items?itemName=BIGModelingTools.umldiagram
* Entity Relationship Modeling in VS Code
https://marketplace.visualstudio.com/items?itemName=BIGModelingTools.erdiagram
-------------- next part --------------
A non-text attachment was scrubbed...
Name: smime.p7s
Type: application/pkcs7-signature
Size: 4236 bytes
Desc: S/MIME Cryptographic Signature
URL: <http://lists.aisnet.org/pipermail/aisworld_lists.aisnet.org/attachments/20230516/6653b4ec/attachment.p7s>