Samuel Erickson Andersson

I am a PhD student at the Division of Decision and Control Systems, advised by Prof. Mikael Johansson (main advisor) and Prof. Cristian Rojas.

I hold a MSc. in Engineering Mathematics from Linköpings universitet, the first year of which I spent at Stanford University as a visiting graduate student. During the spring of 2024 I conducted my master's thesis research at Lynx Asset Management. Prior to my year at Stanford, I obtained a BSc. in Applied Physics and Electrical Engineering, and a BSc. in Mathematics, both from Linköping University.

My research interests span machine learning and optimization, particularly with applications in medicine and finance. I am currently interested in distributed and federated learning. Other topics of interest include statistical learning, high-dimensional statistics, and convex optimization.

Publications

1. S. Erickson and M. Johansson. Personalized Federated Learning Under Model Dissimilarity Constraints. arXiv preprint arXiv:2505.07575 (2025).

2. S. Erickson and T. Rydén. Inverse Covariance and Partial Correlation Matrix Estimation via Joint Partial Regression. arXiv preprint arXiv:2502.08414 (2025).