Tomo Nakamura Laboratory (Graduate School of Information Science, University of Hyogo)
Nonlinear Data Analysis ～the underlying nature of phenomena as interpreted from data (the world we see and know is not all there is)～
Nonlinear Data Analysis ～the underlying nature of phenomena as interpreted from data (the world we see and know is not all there is)～
The world is filled with data. However, data themselves are nothing more than sequences of numbers. On their own they say nothing. To make sense of data, interpretation is required, and interpretation inevitably depends on a framework. A framework is a way of thinking that shapes how we understand data by providing assumptions, structure, and perspective. It gives context to numbers and allows meaning to emerge from them in relation to the surrounding situation and background. When the framework changes, the meaning of the same data may change as well. In this sense, what we call “data analysis” is not merely a collection of techniques but a set of frameworks through which data become meaningful.
My research is centred on this idea of data analysis. Data analysis for me is the practice of using experience, knowledge, data, and computers to discover and solve problems. Much of the data I study change their state over time and across locations. At first glance, data may appear similar, yet in reality each type of data has its own structure and character. Among these, I am particularly interested in phenomena that exhibit complex behaviour involving time delays and nonlinearity.
Ideally, I seek research that does not simply follow established examples or templates. I prefer research that discovers doors that no one else has yet noticed and quietly opens them. I enjoy thinking about ways of thinking themselves and shaping new perspectives for understanding the world. I believe that when one thinks differently from others, something different naturally emerges, and when one thinks in new ways, something new naturally comes into being. In this sense, the “data analysis” I pursue may be seen as a kind of philosophy carried out with mathematics, computers, and data. This description may sound somewhat serious, but even now, as an adult, I try not to lose the curiosity and imagination of childhood. I hope to continue doing research that is imaginative, honest, and just a little mischievous.
Data analysis is an application of mathematics using computers for various phenomena that occur in the real world. Many people may think that mathematics is a study to solve patterns and structures in mathematics. Such a mathematics is called "pure mathematics". I turn various thoughts over in my mind using data observed from phenomena. Also, I develop new methods and try to understand the phenomena and solve problems using various methods with the help of mathematics and computers. My major approaches are following four.
Research keywords: time series analysis, statistical modelling, dynamical system, nonlinear phenomena, optimization problems
