Elias Jarlebring

The field of numerical linear algebra is about algorithms and analysis techniques for large amounts of information and data. These can arise from modeling of various kinds, i.e., abstract descriptions of real phenomena with the help of mathematics. Today, large amounts of information are created in a number of fields and applications, ranging from physics, chemistry and biology, to life science, microelectronics and telecom. One area that has grown in recent years is machine learning in artificial intelligence.

Elias Jarlebring’s research focuses on the development of algorithms, theory, methods and software using numerical linear algebra. The area has an abstract character and often results in universal methods with broad applications. In the development of new algorithms, techniques from adjacent mathematical subjects such as complex analysis, systems theory and probability theory are also used.

The algorithms that are developed are intended to solve real problems and often result in the development of new software. One example is the development of circuit boards designed to reduce energy losses. This requires detailed predictions, including how electromagnetic waves travel in different materials, which leads to large and difficult computational problems that can be solved with numerical linear algebra.