About Conference
We are delighted to announce the fourth International Conference on Optimization and Data Science in Industrial Engineering (ODSIE 2026).
Organized in collaboration with Istinye University in Istanbul, ODSIE 2026 will be held in a fully virtual format, bringing together academics, researchers, educators, industry professionals, and students from around the world. The conference aims to provide a platform for exchanging knowledge, sharing experiences, and presenting the latest theoretical and practical advances in optimization and data science within industrial engineering, encompassing both scholarly research and real-world applications.
Since its inception in 2023, the ODSIE conference series has been held annually, gaining momentum and recognition each year. Reports from previous events are available at:
- ODSIE 2023- 16-17 November: https://odsie2023.refconf.com/page_153.html
- ODSIE 2024- 07-08 November: https://odsie2024.refconf.com/page_234.html
- ODSIE 2025 – 20–23 November: https://odsie2025.refconf.com/will-be-updated/
ODSIE 2026 offers a unique opportunity for experts to address critical national and global challenges in data science and optimization while fostering closer collaborations between academia and industry. Alongside keynote presentations and paper sessions, the conference will feature interactive workshops and other engaging programs, with full details accessible on our website.
We warmly invite researchers, educators, students, and professionals in engineering management and IT. While English is the primary language, papers may be submitted and presented in either English or Turkish. Selected contributions will be considered for publication in journals listed on the conference website.
Submissions focused on Optimization and Data Science are strongly encouraged. The conference welcomes both full papers and abstracts for presentation and inclusion in the proceedings. We accept both theoretical and applied research, including case studies, emphasizing the use of exact and heuristic optimization methods, as well as data science techniques, to support improved decision-making.
→ Suggested topics include, but are not limited to:
- Artificial intelligence and expert systems
- Smart manufacturing
- Sustainable, digital and smart cities
- Heuristic and metaheuristic algorithms with applications
- Big data analytics and Data mining in the industry
- Robotic process automation
- Fintech and algorithmic finance
- Sustainable and circular supply chain management
- Optimization and Data Science in service organizations
- Facilities design and planning
- Transportation and routing
- Inventory planning, Production, and scheduling
- Quality control and reliability engineering
- Project management
- Quantitative finance and risk modeling
- Integrated manufacturing and Enterprise resource planning
- Maintenance planning
- Process/Systems design and improvement
