About Conference
We are pleased to announce the 5th International Conference on Optimization and Data Science in Industrial Engineering (ODSIE 2027).
Organized in collaboration with Istinye University in Istanbul, ODSIE 2027 will be held in a fully virtual format, bringing together academics, researchers, educators, industry professionals, and students from around the world. The conference serves as an international platform for the exchange of knowledge, the sharing of experiences, and the presentation of the latest theoretical and practical advances in optimization and data science within industrial engineering, encompassing both scholarly research and real-world applications.
Since its inauguration in 2023, the ODSIE conference series has been held annually, steadily enhancing its academic visibility and international standing. Reports from previous editions are available at:
ODSIE 2023 – 16–17 November
ODSIE 2024 – 07–08 November
ODSIE 2025 – 20–23 November
ODSIE 2027 provides a valuable opportunity for experts and scholars to address significant national and global challenges in the fields of data science and optimization, while fostering stronger collaboration between academia and industry. In addition to keynote speeches and paper presentation sessions, the conference will feature interactive workshops and other academic programs, with further details available on the conference website.
We cordially invite researchers, educators, students, and professionals in engineering management and information technology to participate in this event. Although English is the official language of the conference, papers may be submitted and presented in either English or Turkish. Selected papers will be considered for publication in journals listed on the conference website.
Submissions in the areas of optimization and data science are highly encouraged. The conference welcomes both full papers and abstracts for presentation and inclusion in the proceedings. Both theoretical and applied research, including case studies, are invited, particularly those emphasizing exact and heuristic optimization methods as well as data science techniques to support more effective decision-making.