ODS 2026 main theme will be ‘Shaping Tomorrow: Optimization and Decision Science for Sustainability’, highlighting how advanced models, algorithms, and quantitative insights can drive responsible, transparent, and forward-looking decisions. The conference emphasizes the crucial role of methodological excellence in addressing environmental, industrial, and societal challenges, inspiring solutions that balance efficiency, resilience, and long-term sustainability.
In keeping with the tradition of ODS conferences, this edition will continue to draw inspiration, ideas, and cross-disciplinary perspectives from applied mathematics, computer science, engineering, economics, and the growing fields of sustainability science and environmental analytics. ODS 2026 will encourage the gathering of scholars and experts from these domains, fostering the exchange of visions, the cross-fertilization of methodologies, and the exploration of emerging challenges.
Building on the heritage of previous ODS events, ODS 2026 aims to serve as a meeting point for academics, practitioners, private companies, public institutions, industries, and independent decision-makers to present approaches and solutions, engage in meaningful knowledge sharing, and showcase impactful applications that support sustainable development.
| April 30, 2026 May 15, 2026 | Deadline for abstracts and short papers |
| May 15, 2026 May 31, 2026 | Acceptance notification |
| June 15, 2026 | Deadline for early registration |
| June 15, 2026 | Deadline to book rooms at Galzignano Resort Terme & Golf at the special participant rate for ODS 2026 (Please note that after June 15, room availability cannot be guaranteed.) |
| July 31, 2026 | Registration deadline for inclusion in the final program |
| September 7-10, 2026 | Conference |
Short paper (8-10 pages, including front matter and references).
Short papers will undergo a review process by anonymous referees. Accepted papers will be included in a special volume of the AIRO Springer Series, indexed in main scientific databases. Short papers must be prepared in LaTeX using this template.
To submit your short paper, please visit the METEOR platform at the link https://meteor.springer.com/ODS2026, register and/or log in, and follow the instructions for the ‘initial paper submission.’ After completing your submission, the platform will automatically send you an acknowledgment email (please also check your spam folder).
Note: If you are presenting your paper in a special session, please indicate the name of the session (e.g., AIROYoung or AI4RAILS) in the "comment for the editor" step when uploading your paper.
Abstract (max 2000 characters, space included).
Abstracts will be selected by the ODS2026 Program Committee to be included in the conference e–book of abstracts. Abstracts must be prepared in Latex using this template.
To complete your submission, rename your TeX file as SpeakerSurname_SpeakerName_ODS2026.tex (e.g. Pacioli_Luca_ODS2026.tex) and submit it using this form (or contacting ods2026@airoconference.it).
After you submit, you will receive an acknowledgment email within few days (please, also check your spam section).
Artificial Intelligence is becoming increasingly integral to the evolution of modern railway systems, supporting advancements in automation, operations and service delivery. As railways embrace digitalisation, AI offers significant opportunities to enhance efficiency, capacity and overall performance. Similar trends can be observed across other sectors such as logistics and manufacturing, where AI adoption continues to deliver substantial benefits. At the same time, the growing use of AI introduces ongoing challenges related to safety, reliability and security that require careful consideration.
Themes and Goals
AI4RAILS workshop is addressing topics related to the adoption of artificial intelligence technologies in railway transport. AI4RAILS is set to showcase AI opportunities over the holistic railway system including traffic planning and management, passenger mobility, predictive maintenance, autonomous driving, transport safety and policy, and including mainline and high-speed railways, metro, tram, and hyperloop. We welcome various applications of AI including machine learning, neural networks and reinforcement learning, evolutionary algorithms, computer vision, large language model (LLM) applications and knowledge-based approaches in railway transport for both freight and passenger transport. Also, both pure AI models as well as hybrid models combining AI and optimization are foreseen.
Topics of interest include, but are not limited to: