The International Conference on Modern Artificial Intelligence and Data Science Systems (MAIDSS) focuses on Artificial Intelligence and Data Science (AI&DS), their applications and how AI&DS fields can support societal challenges such as health and well-being, food and nutrition, agriculture, clean energy, transportation and risk management, for critical issues such as climate change, environmental and ecological protection, societal safety, etc. At the same time, the socio-economic context has also favored the emergence of frauds and other cyber-criminal activities. AI coupled to DS can be used to safeguard and protect users from these kinds of threats. AI&DS are potentially offering solutions to many practical issues of everyday life and if well exploited can positively revolutionize the life of the people.

MAIDSS aims to put in place sustainable mechanisms to strengthen and promote the cooperation between academics and professionals. It is also a key tool for strengthening industrial cooperation in AI R&D and bridging the gap between research and the market.

This Conference is a privileged place to exchange ideas, debates and networking between academics and entrepreneurs around the key issues of research, development and innovation in the various fields of Artificial Intelligence, Data Science and their Applications. This session is therefore intended for start-ups, Designers, Developers, Decision-Makers, Consultants, and of course Master/PhD Students, Researchers and Academics.

Conference Tracks (but not limited to)
Artificial Intelligence (AI) AI in Technology Trends AI in Business AI in Communication AI in Societal Challenges
Cognitive Computing Big Data Business Intelligence Cloud, Fog & Soft Computing Biometrics & Cyber Security
Constraint Programming Blockchain Business Modelling M2M Systems and Services Clean Energy & Environment
Deep Learning Computational Intelligence Business Process Management Mobile Adhoc Networks Climate Change
Expert Systems Computer Vision Data Analysis Mobile Edge Computing Critical Issues
Logic & Fuzzy Logic Data Mining & Web Mining e-Learning Tools Multi Edge Computing Food and Nutrition
Gamification Data Science Enterprise Architecture (EA) Network Evolutions (4G/5G) Health and Well-Being
Information Retrieval Evolutionary Methods Enterprise Engineering Network Function Virtualization Information Security & Privacy
Machine Learning Human Computer Interaction Enterprise Knowledge Engineering Networking & Mobile Apps Medical Diagnosis
Multi-Agent Systems Information Systems Enterprise Knowledge Management Next Generation Networks Privacy in Intelligence
Natural Language Processing IoT & Internet of Everything Enterprise Resource Planning Open Spectrum Solutions Risk Management
Neural Networks Quantum Computing Evolution of EA Satellite Communication Systems Smart Cities
Semantic Web Robotics Service Oriented Architecture SDN & SRN & CRN Smart Services and Platforms
Sentiment Analysis Smart Grid Virtual Organisations Vehicular Networks Social Computing
System of Systems Software Engineering Web Analytics Wireless & Mobile Communication Societal and Private Safety
Virtual & Augmented Reality Video Analysis Web Services Wireless Sensor Networks Transportation


SUBMISSION GUIDELINES

Authors are kindly invited to submit research papers/posters/demo, which are not submitted or published or under consideration anywhere in other conference or journal, either following the link https://easychair.org/conferences/?conf=maidss23 or email at maidss@maidss.org.

Full Papers (10 ~ 12 pages), and short papers (5 ~ 6 pages), written in English, must follow the Springer downloadable template: https://www.springer.com/gp/authors-editors/book-authors-editors/your-publication-journey/manuscript-preparation.

At least two TPC members will review each submission.

The acceptance decision will take into consideration paper relevance, originality, novelty, technical depth, impact, quality, scientific-value added, etc.

The proceedings will be published under the SPRINGER Book Series “Studies in Computational Intelligence“, which is indexed in SCOPUS, DBLP, etc.