Teaching

Undergraduate and graduate courses

In fall 2020 I gave part of the lectures for the Big Data Management course and in spring 2021 for the Large Scale Data Analysis course at the IT University of Copenhagen. The lectures were focused on an overview of data analysis techniques (data preprocessing, visualisation, augmentation) and machine learning models and practices. In spring 2022 I will give the Large Scale Data Analysis course.

During my PhD at Edinburgh University I was a tutor, lab demonstrator, teaching assistant, or marker for the following courses:

  • Algorithmic Foundations for Data Science
  • Introductory Applied Machine Learning
  • Social and Technological Networks
  • Discrete Mathematics and Mathematical Reasoning
  • Data Mining and Exploration
  • Data and Analysis
  • Algorithms and Data Structures
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    I was also a teaching assistant for the Massive Open Online Course (MOOC) Code Yourself! which reached hundreds of thousands of students.

    Supervision - master theses

    A methodological and analytical approach to biodiversity loss Sigrid Olivia Essen

    Unifying cross-platform personal music collections Daniel Bruhn Jensen, Johan Victor Ackerhans

    Spatio-temporal Dependencies in Wind Energy Prediction Anne Havmøller Fellows-Jensen, Sumin Lee

    Maption - making a scalable accessibility instrument Anders Skaaden, Christian Pugholm Andersen, Ola Johannes Rostad Bertoft, Troels Hjarne

    Platform for interactive music exploration Rasmus Dilling Møller, Sean Wachs

    A data driven approach for growing bicycle networks, based on network structure and traffic flow Kristof Gasior

    Experimental evaluation of Federated Learning and its privacy and performance in an application in the Danish wind energy Lukas Krivka, Michal Dang, Teodora-Alexandra Penescu

    Coolwalk Kris Otte, Suvi Majlis Amanda Hänninen

    A machine learning approach using urban land classification to last mile delivery forecasting Emiliano Gustavo Giusto, Ricardo Heber Rangel Valdez

    Customer churn prediction from app use Anne Brix Damgaard Fransen

    Evaluating Self-Supervised Graph Neural Networks using GraphWorld Bertram Wiegand Vilman Kehler, Daniel Enggaard

    Using graph neural networks for predicting wind energy production Nina Sand Horup

    Public engagement

    During my undergraduate degree I volunteered at the Edinburgh Science festival where I helped run one of the Maths workshops that was built around interactive physical games that challenge our understanding of probabilities. Later on, in my PhD, together with other students I gave the Game On! workshop that has been running for 5 years and taught hundreds of children how to build their first computer game. I later on continued working with children, teaching the after school Computing Club to students at Bruntsfield Primary School. An adapted version of the material was taught at a workshop during Innovative Learning Week at Edinburgh University, aimed at university students and staff wanting to learn how to code, as well as at Sutton Trust summer school for high-achieving students from disadvantaged backgrounds.