My CV

Contact Details

Feel free to email me (address below) if you need more than just my email.

Education

Ph.D. Computational Linguistics, 2019–2023

University of Groningen

• Research topic: Improving neural machine translation for low-resource languages
• Advisors: Dr. Antonio Toral, Prof. Gertjan van Noord

M.Sc. Artificial Intelligence, 2017–2019

University of Groningen

• Master’s thesis on unsupervised neural machine translation under advisors Dr. Antonio Toral and Dr. Jennifer Spenader
• Relevant coursework:
  • Natural Language Processing
  • Machine Learning
  • Deep Learning

B.Sc. Computer Science, 2016–2017

Indiana University

• Graduated with Highest Honors with a 3.97/4.0 GPA
• Relevant coursework:
  • Computer Vision
  • Summer Research in Computer Vision
  • Machine Learning

Computer Science Major, 2012–2016

University of Puget Sound

• Bachelor’s project on automatic reference-finding in the Latin Vulgate
• Relevant Coursework: Natural Language Processing

Publications

Google Scholar, if you prefer

• Lukas Edman, Antonio Toral, and Gertjan van Noord. Subword-Delimited Downsampling for Better Character-Level Translation, Findings of the Association for Computational Linguistics: EMNLP 2022. 2022.
• Lukas Edman, Antonio Toral, and Gertjan van Noord. Patching Leaks in the Charformer for Efficient Character-Level Generation, arXiv preprint arXiv:2205.14086. 2022.
• Lukas Edman, Antonio Toral, and Gertjan van Noord. The Importance of Context in Very Low Resource Language Modeling, 18th International Conference on Natural Language Processing (ICON2021). 2021.
• Lukas Edman, Ahmet Üstün, Antonio Toral, and Gertjan van Noord. Unsupervised Translation of German–Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language, EMNLP 2021 Sixth Conference on Machine Translation (WMT21). 2021.
  • Achieved first place for Lower Sorbian→German translation
• Lukas Edman, Antonio Toral, and Gertjan van Noord. Low-Resource Unsupervised NMT: Diagnosing the Problem and Providing a Linguistically Motivated Solution, The 22nd Annual Conference of the European Association for Machine Translation (EAMT2020). 2020.
• Lukas Edman, Antonio Toral, and Gertjan van Noord. Data Selection for Unsupervised Translation of German–Upper Sorbian, EMNLP 2020 Fifth Conference on Machine Translation (WMT20). 2020.
• Christian Roest, Lukas Edman, Gosse Minnema, Kevin Kelly, Jennifer Spenader and Antonio Toral. Machine Translation for English–Inuktitut with Segmentation, Data Acquisition and Pre-Training, EMNLP 2020 Fifth Conference on Machine Translation (WMT20). 2020.
• Antonio Toral, Lukas Edman, Galiya Yeshmagambetova, and Jennifer Spenader. Neural Machine Translation for English–Kazakh with Morphological Segmentation and Synthetic Data, ACL 2019 Fourth Conference on Machine Translation (WMT19). 2019.
  • Achieved first place for English→Kazakh translation

Work Experience

Instructor, 2017–2023

University of Groningen

• Gave lectures on Unsupervised NMT and Machine Learning for NLP, Computer Vision, and Audio Processing
• Led tutorial and computer lab sessions
• Wrote and graded coursework
• Invigilated and graded exams
• Supervised students on projects for conference shared tasks
• Courses taught (Bachelor):
  • Machine Learning Project, 2021–22
• Courses assisted (Master):
  • Shared Task Information Science, 2020–22
  • Language Technology Project, 2020–22
  • Natural Language Processing, 2018–19
  • Pattern Recognition, 2018–19
• Courses assisted (Bachelor):
  • Machine Learning Project, 2020–21
  • Advanced Algorithms and Data Structures, 2018–19
  • Artificial Intelligence I, 2017–19

Thesis Supervisor, 2020–2021

University of Groningen

• Supervised Master’s student on their thesis project.
• Research on Unsupervised NMT for English–Chinese

Reviewer, 2019–2023

University of Groningen

• Reviewed academic papers for ICON2021, EMNLP2022.
• Co-reviewed several academic papers with Dr. Antonio Toral for WMT19, *SEM 2019, EAMT 2020, WMT20, and MT Journal.

Technical Skills

• Programming Languages
  • Currently using: Python, Shell
  • Prior experience with: Java, JavaScript, C
• Software and Libraries
  • Currently using: PyTorch, HuggingFace
  • Prior experience with: TensorFlow, Keras