Supervision:

In this page you can see the projects/topics that I have supervised and the ones that I am currently supervising. MT and FT stand for Master thesis and Free Topic, respectively. Students doing their M.S. thesis have, in some cases, been collaborating with companies, such as EyeJustRead, Telenor, PLX AI ApS, Ramboll, PlantJammer, Ambu and Achmea.

Current projects:

  • (MT) Biases in Language Models in Danish
  • (MT) Automatic generation of music and lyrics
  • (MT) Automatic generation of music and art
  • (MT) Clustering the Pitch: Unsupervised Learning Techniques for Defining Game Scenarios in Football Matches
  • (MT) Computational Creativity in Text-Based Adventure Games - Leveraging Machine Learning in Procedural Content Generation to improve Gameplay experience
  • (MT) Short-term time perception
  • (MT) Hebbian learning applications
  • (FT) Chaos Theory applications

Previous projects:

  • (MT) Automatic generation of Song Ci-poetry using neural networks
  • (MT) Automatic crochet pattern instruction generation (Link to thesis from the Royal Library)
  • (MT) Analyzing the effects of Virtual Reality in comparison to psychedelics (Link to thesis from the Royal Library)
  • (MT) Personalized news headline generation
  • (MT) Style change detection in Chinese language
  • (MT) Using NLP for the analysis of Covid-19 related tweets
  • (MT) Using stereophonic guiding to help people
  • (MT) Using RNNs for rap lyrics generation (Link to thesis from the Royal Library)
  • (MT) Towards fair Venture Capital
  • (FT) Automatic music generation
  • (MT) Analysis of the social concept of class examining word embedding models
  • (MT) Extracting texts from charts and plots (Link to thesis from the Royal Library)
  • (MT) Medical information Extraction
  • (MT) Automatic summarization of texts (Link to thesis from the Royal Library)
  • (MT) Authorship verification and analysis in Danish news articles (Link to thesis from the Royal Library)
  • (FT) Automatic morphological inflection
  • (MT) Intelligent fashion generation
  • (MT) Children’s Storybook Generation (text and images)
  • (MT) Deception detection using language, sound and gestures
  • (MT) Audiovisual Salience Model
  • (MT) Image analysis for medical purposes
  • (MT) Language Identification of the Iberian Languages
  • (MT) Marine safety assisted by Data Science
  • (MT) Recommender systems for recipes
  • (MT) Automatic Analysis and Generation of perfumes
  • (MT) Extraction of environmentally related news and information from unstructured data
  • (FT) Topic Modelling for Automatic Text Classification
  • (MT) Automatic generation of humor
  • (MT) Spiking neurons and Neural Networks
  • (FT) Automatic rhythmic analysis of chinese poetry
  • (MT) Music Generation and Deep Learning
  • (MT) Business Intelligence and user modeling based on data
  • (MT) Word Sense Disambiguation and Induction
  • (MT) Question Answering using Reinforcement Learning
  • (MT) Automatic generation of Rap lyrics
  • (MT) Automatic generation of Sonnets
  • (MT) Towards automatic fluency detection on sentence readings: Scanpath measures on real-world data of children with reading difficulties.
  • (MT) Machine Learning classification of self-reported depression diagnosed users on social media.
  • (MT) Automatic POS tagging in poetry