CV

PhD in Computer Science

• Deep generative models and feature selection with applications to fluid mechanics at RPL.

MSc in Applied Mathematics

• Courses in mathematics, statistics, machine learning, optimization etc.
• Thesis titled "Towards Alignment-Free Phylogenetic Inference: Variational Inference in the Thorne–Kishino–Felsenstein Model of Sequence Evolution".

BSc in Computer Science

• Courses in mathematics, computer science, algorithms, software engineering etc.
• Thesis titled "Bayesian Parameter Tuning of the Ant Colony Optimization Algorithm: Applied to the Asymmetric Traveling Salesman Problem"

Doctoral Researcher

• Deep generative models and feature selection with applications to fluid mechanics at RPL.

Research Assistant

• Probabilistic machine learning applied to phylogenetic inference at Lagergren Lab.
• Deep generative models applied to optimal sensor placement at RPL.

IT Intern

• Worked part time and summers at one of Sweden's major banks.
• Automated regulatory information, maintaining a large codebase in Python.

Teaching Assistant

• DD2424 Deep Learning in Data Science
• DD2412 Deep Learning, Advanced Course
• DD2350 Algorithms, Data Structures and Complexity
• DD1362 Programming Paradigms
• DD1331 Fundamentals of Programming

Student Ambassador

• Student recruitment through presentations and representing KTH at education fairs.

• ICML 2024 Workshop on Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators

OxML Summer School 2024

RPL Summer School 2024

Reception Buddy

• Welcomed new KTH-students to the Computer Science Chapter 2019 and 2020.

Project Group

• D-Dagen is an IT-career fair. In 2019, 81 companies and over 2000 guests attended.
• Managed contacts with attending companies and led a team of staff during the fair.

• Henrik Göransson Sandviken Stipend.