Scope
In this age of data-driven change, humanity is confronted with fresh challenges that redefine our lifestyles, work processes, and the progression of social civilization. The I-DO 2026 initiative seeks to unite academic researchers and industry experts from a wide range of disciplines to promote collaboration and research on data-related issues across different fields.
The I-DO 2026 conference serves as a global platform where eminent scientists, engineers, researchers, practitioners, educators, and students can showcase their recent discoveries, share fresh ideas, and engage in discussions about technological improvements in Information Technology, Data Science, and Optimization. By fostering collaboration and enabling the sharing of knowledge and experiences across these interconnected fields, the conference aims to encourage innovation and accelerate advancements in science and technology.
We invite contributions that showcase novel and unpublished research, encompassing new theories, methodological breakthroughs, practical uses, case investigations, and contributions that are still in progress. The detailed program will include keynote addresses, workshops, technical sessions, poster displays, and a doctoral consortium, all offering extensive opportunities for scholarly and professional engagement.
Highlights
• Brings together researchers, engineers, and practitioners from Information Technology, Data Science, and Optimization to promote interdisciplinary collaboration and knowledge exchange.
• The accepted submissions will be published as part of the Lecture Notes in Computer Science (LNCS) proceedings series, which is among the largest scientific libraries globally.
• The proceedings of I-DO are listed in major indexing services such as Scopus, WoS, DBLP, EI Compendex, Google Scholar, and others.
• Authors of selected best accepted papers will be invited to submit an extended version to the following SI: JISE (SCIE), JIT (SCIE), Electronics (SCIE)
Conference topics
This conference addresses a range of topics, from established research areas to new trends in Information Technology, Data Science, and Optimization. It also explores related interdisciplinary fields. Key themes of interest encompass a variety of subjects, including, but not restricted to, the themes listed below:
• Theme 1: Big Data – Data acquisition, storage, management, analytics, and visualization for large-scale and complex datasets.
• Theme 2: Computer Graphics and Visual Analytics – Data visualization, interactive graphics, and human-computer interaction for insight discovery.
• Theme 3: Data-Based Systems and Interfaces – Intelligent systems, user interfaces, and platforms driven by data-centric approaches.
• Theme 4: Data Science – Machine learning, artificial intelligence, statistical modeling, and data-driven decision-making.
• Theme 5: Optimization – Theories, algorithms, and applications of mathematical and computational optimization in engineering, management, and science.
Venue
National Pingtung University, Pingtung, Taiwan. (https://www.nptu.edu.tw/)