A presentation of our newly employed colleagues.

## Jenny Enerbäck

### Project Assistant at the Division of Applied Mathematics and Statistics

Start date: November 25, 2024

## Helga Kristín Ólafsdóttir

### Postdoctor at the Division of Applied Mathematics and Statistics

Start date: November 4, 2024

## Jakob Palmkvist

### Senior Lecturer at the Division of Algebra and Geometry

My research interests lie in the areas of algebra and mathematical physics. In particular, I am interested in extensions of Kac-Moody algebras to infinite-dimensional integer-graded Lie superalgebras and related structures with applications to supergravity theories.

I have previously worked at the Max Planck Institute for gravitational physics, Université Libre de Bruxelles, IHÉS, Texas A&M University and at the Department of Physics at Chalmers. I have also been a guest lecturer at Mathematical Sciences.

Start date: November 1, 2024

## Adrien Malacan

### PhD student at the Division of Analysis and Probability Theory

My research will focus on the study of the properties of lattice gauge theory under the supervision of Malin P. Forsström. The aim of the project is to apply probabilistic methods to gain a better understanding of this model, which has applications notably in quantum physics. An interesting aspect of the research is examining how this model behaves compared to similar discrete models (such as the Ising model).

I completed my master’s degree in mathematics at the Technical University of Munich, where my master’s thesis explored the simple exclusion process, a model in discrete probability theory.

Start date: October 1, 2024

## Andrii Dmytryshyn

### Associate professor at the Division of Applied Mathematics and Statistics

My research interests primarily lie in the fields of matrix theory and computations, as well as their applications in computer science and physics. Specifically, I focus on linear and non-linear eigenvalue problems, matrix equations, and low-rank structures.

Before joining Chalmers, I worked and studied in Örebro, Umeå, Bordeaux, Padua, and Kyiv.

Start date: October 1, 2024

## Maia Emmerö

### Akelius Math Learning Lab

Start date: September 16, 2024

## Laleh Varghaei

### PhD student at the Division of Applied Mathematics and Statistics

My research is in bioinformatics and artificial intelligence. The research will be carried out in Erik Kristiansson's research group with a focus on antibiotic resistance. We will use large amounts of genomic and metagenomic data to track antibiotic resistance genes between different bacteria and understand the environments in which they are selected.

Previously I studied Bioengineering for my bachelor’s degree at Chalmers and for my master’s, I studied engineering mathematics and computational science at the same university. My master thesis focused on developing methods to study genetic diversity and evolutionary patterns in Human Immunodeficiency Virus (HIV) using sequencing data, bioinformatics tools and machine learning.

Start date: September 1, 2024

## Lucia Swoboda

### PhD student at the Division of Applied Mathematics and Statistics

My research area is the numerical analysis of partial differential equations, where I am particularly interested in problems involving different scales. Under the supervision of Axel Målqvist, I will be working on multilevel methods for spatial network models. Previously, my main focus was on space-time methods for the heat equation, using a modified Hilbert transform to analyse a Galerkin-Bubnov variational formulation in anisotropic Sobolev spaces. I received a master’s degree in mathematics from Graz University of Technology and the University of Graz.

Start date: August 27, 2024

## Paolo Boldrini

### PhD student at the Division of Analysis and Probability Theory

Start date: August 23, 2024

## Caitlin Canavati

### Akelius Math Learning Lab

Start date: August 26, 2024

## Jakob Jonsson

### PhD student at the Division of Analysis and Probability Theory

I am interested in harmonic analysis, partial differential equations and wavelets. Supervised by Andreas Rosén I will try to generalise my master's thesis work, where we developed a wavelet-based method to solve boundary value problems numerically.

I took my bachelor's degree in Linköping and my master's degree here at the University of Gothenburg.

Start date: August 23, 2024

## Emil Timlin

### PhD student at the Division of Applied Mathematics and Statistics

My research will be about the homogenization of partial differential equations, and the project is supervised by Irina Pettersson and Tobias Gebäck. In this field, one is interested in differential equations whose coefficients are rapidly oscillating. The goal is to replace such an equation with a suitable homogenized equation which is easier to solve, but that still models the same macroscopic phenomenon as the original equation.

I have studied at Chalmers and University of Gothenburg. In my master thesis, I investigated new methods for numerically solving boundary value problems.

Start date: August 23, 2024

## Mika Persson

### Industrial PhD student at the Division of Applied Mathematics and Statistics

I'm an industrial PhD student affiliated with SAAB. My research focuses on game theory and multi-agent reinforcement learning for distributed sensors playing information games for enhanced situational awareness. This involves partially observable Markov games with heterogeneous and varying number of players, multi-target tracking, robust data fusion and deep learning. The project is funded by Wallenberg AI, Autonomous systems and Software Program (WASP) and is connected to the WASP research arena in Public Safety (WARA-PS).

I have a master's degree in engineering mathematics with a specialization in machine intelligence from Lund University and have previously worked as a systems engineer at SAAB, where I developed radar signal processing algorithms.

Start date: August 19, 2024

## Oskar Holmstedt

### PhD student at the Division of Applied Mathematics and Statistics

I will be conducting research on stochastic modeling of infectious diseases under the supervision of Philip Gerlee. The goal of the research is to develop methods for estimating transmission chains within a population using Bayesian inference. Specifically, these methods will be applied to data from hospital environments, with the long-term goal of being used in healthcare to combat and control infectious outbreaks.

I have a Master of Science in Engineering Mathematics from Chalmers. My master's thesis focused on using neural networks to calculate the likelihood function in the context of Bayesian inference.

Start date: August 19, 2024

## Styrbjörn Käll

### PhD student at the Division of Applied Mathematics and Statistics

I will work in Erik Kristiansson's research group where I will be studying toxicology and diagnostics using artificial intelligence and bioinformatics. I will for example develop transformer-based methods that, at an early stage, can predict chemicals' threat to the environment and humans based on their structure, as well as methods to rapidly predict the cause of an infection based on biomarkers in synovial fluid.

I have previously worked as a Data Scientist at Semcon and as a project assistant here at the Math department. I have a master's and bachelor's degree in biotechnology from Chalmers.

Start date: August 19, 2024

## Sophia Axillus

### PhD student at the Division of Applied Mathematics and Statistics

My research will focus on integrating bioinformatics and artificial intelligence to enhance our understanding of antibiotic resistance and the emergence of new resistance genes. It will involve DNA sequence analysis, biological network inference, and evolutionary modeling. The work will be carried out in the group of Erik Kristiansson.

I previously worked at AstraZeneca as a Data Science & AI graduate scientist. Before then I studied Bioengineering at Chalmers, graduating with an MSc in Engineering Mathematics and Computational Sciences.

Start date: August 19, 2024

## Lotta Eriksson

### PhD student at the Division of Applied Mathematics and Statistics

My project is in computational biology and is supervised by Eszter Lakatos. My research focuses on developing novel mathematical and bioinformatics methods to identify key factors behind cancer and disease development using next-generation sequencing (NGS) data

I previously studied Engineering Mathematics at Chalmers, and wrote my master’s thesis about denoising methods for NGS data from liquid biopsies to discover genomic alterations caused by cancer.

Start date: August 19, 2024

## Seif Sharif

### PhD student at the Division of Algebra and Geometry

Start date: August 15, 2024

## Anna Theorin Johansson

### PhD student at the Division of Algebra and Geometry

I will be studying analytic number theory under the supervision of Julia Brandes. In particular, we aim to study applications of the Harvey-Littlewood circle method – a method to count the number of solutions of Diophantine equations, which can be applied to many different kinds of mathematical problems (e.g. Waring’s problem).

I studied mathematics at ETH Zürich and the University of Edinburgh and wrote my master thesis on Zaremba’s conjecture and the circle method.

Start date: August 15, 2024

## Andreas Krona

### Akelius Math Learning Lab

I am educated in engineering, creativity, economics, and leadership, with work experience in fields ranging from film and video games to AI and food. My tasks have, among others, included development, sales, and leadership.

Through my work at Akelius Math Learning Lab, I hope to contribute to creating a memorable mathematics education that can help make the world at least a little better.

Start date: August 5, 2024

## Mattias Lennartsson

### Part-time fixed-term teacher at the Division of Algebra and Geometry

Start date: August 1, 2024

## Niki Wilhelmson

### PhD student at the Division of Applied Mathematics and Statistics

I will study topics within machine learning under the supervision of Pierre Nyquist. Using tools from probability theory, and related areas, the goal is to contribute to our understanding of the mathematical principles underlying modern methods for machine learning and artificial intelligence.

I studied the Engineering Physics programme at KTH Royal Institute of Technology, with a master’s in applied mathematics, and wrote my master thesis on Bayesian methods for covariance estimation in finance.

Start date: August 1, 2024

## Malin Rau

### Assistant Professor at the Division of Applied Mathematics and Statistics

My research has two main focuses. The first is developing Approximation Algorithms and proving lower bounds for Scheduling and two-dimensional Packing Problems. For these algorithms, linear and integer programs and results about the structure of optimal solutions play an essential role.

My second research focus is on random processes within graph structures, specifically studying opinion dynamics, load-balancing processes, and group testing.

After receiving my PhD at Kiel University (CAU), I was a PostDoc at the Université Grenoble Alpes (UGA) and later a PostDoc at the Universität Hamburg.

Start date: August 1, 2024

## Mathis Rost

### PhD student at the Division of Applied Mathematics and Statistics

I will be studying spatial statistics under the guidance of Ottmar Cronie, with a focus on point processes. This area of study involves analyzing spatial point patterns, which has applications in various fields such as epidemiology and ecology.

I completed my mathematics degree at Ulm University, where I also developed a strong foundation in computer science. I wrote my master thesis on point processes and spatial statistics at the Department of Mathematical Sciences within the ERASMUS program.

Start date: June 3, 2024

## Hilda Alfredsson

### Akelius Math Learning Lab

Start date: April 29, 2024