Artificial Intelligence (AI) research has broad applications in real-world problems. Examples include control, planning and scheduling, pattern recognition, knowledge mining, software applications, strategy games and others. The ever-evolving needs in society and business both on a local and on a global scale demand better technologies for solving more and more complex problems. Such needs can be found in all industrial sectors and in any part of the world.
The Multi-disciplinary International Conference on Artificial Intelligence (MIWAI), formerly called The Multi-disciplinary International Workshop on Artificial Intelligence, is a well-established scientific venue in the field of artificial Intelligence. MIWAI was established more than 17 years ago. This conference aims to be a meeting place where excellence in AI research meets the needs for solving dynamic and complex problems in the real world. The academic researchers, developers, and industrial practitioners will have extensive opportunities to present their original work, technological advances and practical problems. Participants can learn from each other and exchange their experiences in order to fine-tune their activities in order to help each other better. The main purposes of the MIWAI series of conferences are:
Artificial intelligence is a broad area of research. We encourage researchers to submit papers in the following areas but not limited to:
The Secure Edge-AI (SEAI) special session aims to explore the intersection of artificial intelligence (AI) and edge computing with a focus on security, privacy, and resilience. As AI-powered edge devices proliferate across industries such as healthcare, autonomous systems, IoT, and smart cities, ensuring their security and robustness is crucial.
We welcome submissions on topics including, but not limited to:
The AI in Industry (AIIN) special session aims to explore the use of AI and digital transformation (DX) in industry. Applications such as AI-powered systems for quality control, safety and security monitoring systems in manufacturing, smart manufacturing, fintech and economics applications are essential.
We welcome submissions on topics including, but not limited to:
This tutorial introduces the audience to the application of Generative AI (GenAI) for processing multimedia documents in small and medium-sized healthcare facilities. The presenters, including healthcare providers and GenAI researchers, will demonstrate how GenAI can manage information efficiently.
In developing countries like India, many clinics face challenges due to limited IT infrastructure, relying on handwritten or printed prescriptions and discharge sheets. The absence of structured databases complicates healthcare management. Additionally, radiologists and diagnostic professionals often dictate their findings, which are transcribed by secretaries. Training and maintaining qualified staff is another challenge for these clinics.
Generative AI offers a promising solution by digitizing handwritten, printed, and voice data from physicians, which can then be stored in a structured data warehouse. Our initiative involves collecting over a hundred voice and paper documents to build a comprehensive database that can be queried using natural language. This approach aims to streamline data management in clinics, enhancing the overall efficiency and accuracy of healthcare delivery.
The tutorial will depict various scenarios in SME healthcare facilities and present corresponding multimedia documents. We will demonstrate how different GenAI technologies can effectively process these documents. While the solutions described will increase the efficiency of information processing in healthcare facilities, there are challenges that make full automation difficult. We will identify these challenges in the multimedia documents, opening up new directions for further research.
This tutorial provides a hands-on introduction to text analytics using Python, focusing on NLP fundamentals, practical use of libraries like NLTK and spaCy, and sentiment analysis techniques. Designed for researchers, postgraduate students, and NLP beginners, the session equips participants with essential skills in processing unstructured textual data. Key topics include tokenization, stemming, lemmatization, POS tagging, and real-world sentiment analysis applications.
For more details, please click here to download.
Submission link: https://www.easychair.org/conferences/?conf=miwai2025
Both research and application papers are solicited. All submitted papers will be carefully peer-reviewed on the basis of technical quality, relevance, significance, and clarity.
Each paper should have no more than twelve (12) pages in the Springer-Verlag LNCS style. The authors' names and institutions should not appear in the paper. Unpublished work of the authors should not be cited. Springer-Verlag author instructions are available at: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
| Event | Date |
|---|---|
| Submission Deadline | July 15, 2025 |
| Notification Deadline | August 1, 2025 |
| Camera Ready Deadline | August 15, 2025 |
| Registration Deadline | August 22, 2025 |
| Conference Dates | December 3-5, 2025 |
