Lauri Heinonen

- Doctoral Candidate, Statistics (Department of Mathematics and Statistics)
- Teacher, Department of Mathematics and Statistics (Department of Mathematics and Statistics)
lauri.k.heinonen@utu.fi ORCID identifier: https://orcid.org/0000-0001-6357-0041 |

dimensionality reduction; kernel methods; statistical learning

I started studying at the University of Turku, Department of Mathematics and Statistics in 2015 and graduated in 2021 with Master of Science in statistics. I have always been interested in both statistics and mathematics and studied them both equally. My master’s thesis “Ydinmenetelmä riippumattomien komponenttien analyysiin" (Kernel Method for Independent Component Analysis) is about applying the principles of Kernel principal component analysis into Independent component analysis. Since 2022, I have been working on my dissertation where I continue with the themes of kernel methods and dimensionality reduction.

My current research is about using for example the framework of kernel methods to develop new non-linear robust and sparse methods for dimensionality reduction. I combine both theoretical study and method development, and computational evaluation of methods using simulations.

At the moment, I act as a teacher tutor for students and in spring 2023 I organized exercise sessions for the course Multivariate methods. During the year 2023, I am also taking the course Basics in University Pedagogy. Before, I have lectured the courses Basics of Abstract Mathematics and Mathematical Writing, and taught one of the topics in the Advanced Course in Statistical Learning. I addition to that, I have organized exercise sessions for many courses.