About

I am a Ph.D. student in the algorithms group at the IT University of Copenhagen under the supervision of Martin Aumüller and co-supervisor Arthur Zimek.

My academic journey began at the University of Copenhagen where I completed my Bachelor’s and Master’s degrees. My background in physics provided me with a solid foundation in programming from creating simulations of physical systems to statistical analysis and data processing. In particular I worked on a project as part of the applied machine learning course which provided me with experience in areas such as data pre-processing, constructing convolutional neural networks as well as visualizing and communicating scientific results.

Presently I am studying algorithms and data structures for approximate near neighbor searches. The goal of my project is to design algorithms that are both scalable and robust and can be used for classification, clustering and outlier detection. In addition to this my project will involve studying the quality and efficiency of such algorithms.

Research

• The current focus of my research is the DBSCAN algorithm and Locality Sensitive Hashing (LSH). I am working on developing an algorithm that combines DBSCAN with an implementation of LSH. This is with the aim of creating a more efficient DBSCAN algorithm for very large and high-dimensional data.

Teaching

Classes at the IT University of Copenhagen

• • Autumn 2023: Advanced Algorithms

Classes at University of Copenhagen

• • Spring 2020: Statistical Physics’s