Courses


Training Schools


Demonstrating


MS and BS Student Supervision


  • Wojciech Ostrowski, MSc in Computer Science student at the University of Copenhagen, "Generating Fact-Checking Explanations" (co-supervised by Pepa Atanasova, 2020). Paper based on MSc thesis accepted to IJCAI 2021. [Paper]
  • Lukas Muttenthaler, MSc in IT and Cognition student at the University of Copenhagen, "Subjective Question Answering" (co-supervised with Johannes Bjerva, 2020). Publication in BlackBoxNLP workshop at EMNLP. [Paper]
  • Marcus Hansen, BSc in Computer Science student at the University of Copenhagen, "Text Mining and Processing on Patients Experiences on Psilocybin" (co-supervised by Melanie Ganz-Benjaminsen, 2020)
  • Jimmie Jin, Asger Thorleif Knudsen, Sylvester Lee, BSc in Computer Science students at the University of Copenhagen, "Stance Detection of Climate Change Tweets" (co-supervised by Dustin Wright, 2020)
  • Sebastian Hansen, Bjørn Møller, William Hansen, BSc in Computer Science students at the University of Copenhagen, "Graph Convolutions on Co-Author Networks" (co-supervised by Andreas Nugaard Holm, 2020)
  • Yi He and Mihai Popovici, MSc in Computer Science student at the University of Copenhagen, "Stance Detection in Scientific Reviews" (co-supervised by Rahul Aralikatte, 2019)
  • Haining Tong, MSc in Computer Science student at the University of Copenhagen, "Zero-Shot Relation Extraction via Description Learning" (co-supervised by Matt Lamm, 2019)
  • Zhong Xuan Khwa, BSc in Computer Science student at the University of Copenhagen, "Zero-Shot Relation Extraction using Graph Neural Networks" (co-supervised by Selvan Raghavendra, 2019)
  • Raluca Alexandra Fetic, MSc in IT and Cognition student at the University of Copenhagen, "Learning to encode large documents efficiently for stance detection" (2019)
  • Andrea Lekkas and Magnus Alexander Johansen, MSc in Computer Science students at the University of Copenhagen, "Learning to ask questions about products" (2018). Andrea is now a PhD student affiliated with CopeNLU.
  • Peter Spliid, MSc in Computer Science student at the University of Copenhagen, "A Framework for Typological Evaluation of Language Representations" (co-supervised by Johannes Bjerva, 2018)
  • Leendert Bastian van Doorn, MSc in Computer Science student at the University of Copenhagen, "Variational encoding of location for dialect-conditional language generation" (co-supervised by Johannes Bjerva, 2018)
  • Ke Zhai, MSc in Computer Science student at the University of Copenhagen, "Deep Learning of Linguistic Features for Scandinavian Languages" (co-supervised by Johannes Bjerva, 2018)
  • Christoffer Trysøe, Andreas Borgstad and Xuwen Zhang, MSc in Computer Science students at the University of Copenhagen, joint project on "Modelling customer behaviour from clickstream data" (with Fabian Gieseke, 2018)
  • Thomas Nyegaard-Signoria and Casper Veistrup Helms, BSc in Computer Science students at the University of Copenhagen, joint project on "Modelling affect in tweets" (co-supervised by Johannes Bjerva, 2017). Participated in Semeval 2018 Task 1. [Paper]
  • Rogan Inglis, MSc in Machine Learning student at University College London, "Machine Reading for Scientific Publications Using Generative Regularisation" (co-supervised by Pasquale Minervini, 2017)
  • Benjamin Riedel, MSc in Machine Learning student at University College London, "Simple yet powerful: A system for news article stance detection" (with George Spithourakis, Sebastian Riedel, 2017). Won second place in Fake News Challenge. [Paper]
  • Danish Sheikh, Computer Science MEng student at University College London, "Extracting Keyphrases and Relations from Scientific Publications" (with Sebastian Riedel, 2017)
  • Rupert Chaplin, MSc in Machine Learning student at University College London, "End-to-end Differentiable and Interpretable Deep Learning for Natural Language Programming" (with Tim Rocktäschel, Sebastian Riedel, 2016)
  • Dhruv Ghulati, MSc in Computer Science student at University College London, "Distant Supervision and Cost Sensitive Classification for Weakly Supervised Claim Detection" (with George Spithourakis, Andreas Vlachos, Sebastian Riedel, 2016. Follow-up funding of project provided by Google, see Guardian article.)