In the last 10 years, novel measurement technologies are rapidly emerging in many scientific fields including astronomy, physics, quantum mechanics, nanoscopy, medicine, biology, ecology and sociology. They enable the measurements on various objects beyond their past limits on accuracy, resolution and sensitivity of their outcomes, and size, distance, quantity, structure and feature of the objects. They are now largely thrusting the scientific innovation. On the other hand, these technologies rely on not only their hardware instrument technologies but also the analysis techniques for their measurement data. In many cases, the information on the objects must be estimated by processing measurement outcomes and by applying some prior information.

These estimation tasks must be effectively conducted by applying the recent progress of statistics, machine learning and pattern recognition including some novel principles adapted to the measurement problems. Based on these backgrounds, this special session aims to establish a new DSAA research field named “Mathematical Information Measurement Science (MIMS),” and calls for papers on such innovative work on the statistical, machine learning and pattern recognition techniques developed for the advanced measurements and their applications to the advanced measurement problems.