The amount of data in the world is increasing enormously all the time. One of the fundamental paradigms of computer science is how to process data automatically. Data science is an interdisciplinary field focused on extracting knowledge from data sets. Data science applies the knowledge and insights from data to solve problems in various application domains.
The central goal of data analysis is to form information and models from the collected data based on the behaviour of the data. Using the created models' data can be interpreted. Modern data analysis takes place in many situations using machine learning methods. Data analysis and machine learning are based on statistics, linear algebra, probability theory, information theory, differential and integral calculus, and numerical methods.
Computational data science research bridges traditional computational science and data science. Data-based modelling benefits significantly by doing things resource-wise, using methods developed over history. Some of these methods are the results of pure mathematics, while some are based on mathematical physics. Especially in situations where there is little data, it is necessary to find methods that can be used to generalize the developed models to larger samples. Traditional mathematical models can help provide answers more efficiently (regarding computational cost, data amount, or model accuracy).
The research group develops machine learning methods and methodology, which is applied interdisciplinary both at the Ä¢¹½Ö±²¥ and outside of it. There are several application areas where the research group is currently active, especially in spectral imaging, machine vision, health science and data-driven process modelling. The research group operates in two laboratories. Spectral Imaging Laboratory provides hyperspectral imaging and analysis research using state-of-the-art modelling, simulation and machine learning methods. Digital Health Intelligence Laboratory is to develop intelligent, data-driven solutions to real-world problems central to promoting human health and wellbeing.
