Summer Semester 2024

Intelligent Systems

  • 8 LP
  • undergraduate, graduate

Reproducible Machine Learning

  • 8 LP
  • undergraduate, graduate

Tool-Augmented Large Language Models

  • 8 LP
  • undergraduate, graduate

Introduction to Neural Networks and Sequence-To-Sequence Learning

  • 8 LP
  • undergraduate, graduate

Research Module for MA-Students

  • 20 LP
  • graduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Winter Semester 2023/24

LECTURE

Mathematical Foundations

  • 6 LP
  • undergraduate

LECTURE

Statistical Methods for Computational Linguistics

  • 6 LP
  • undergraduate

PROJECT

Software Project

  • 6+4 LP
  • undergraduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Summer Semester 2023

MAIN SEMINAR

Introduction to Neural Networks and Sequence-To-Sequence Learning

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Robust and Parameter-Efficient Finetuning

  • 8 LP
  • undergraduate, graduate

PROJECT

Software Project

  • 6+4 LP
  • undergraduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Winter Semester 2022/23

LECTURE

Mathematical Foundations

  • 6 LP
  • undergraduate

LECTURE

Statistical Methods for Computational Linguistics

  • 6 LP
  • undergraduate

MAIN SEMINAR

Interpretable ML

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Invariant Learning and Disentanglement for NLP

  • 8 LP
  • graduate

PROJECT

Research Module for MA-Students

  • 20 LP
  • graduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Summer Semester 2022

MAIN SEMINAR

Neural Machine Translation

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Empirical Methods for NLP and Data Science

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Vision and Language Navigation

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Introduction to Neural Networks and Sequence-To-Sequence Learning

  • 8 LP
  • undergraduate, graduate

PROJECT

Software Project

  • 6+4 LP
  • undergraduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Winter Semester 2021/22

PREPARATORY COURSE

Introduction to Resources in CL

  • (no credit points)
  • undergraduate

LECTURE

Statistical Methods for Computational Linguistics

  • 6 LP
  • undergraduate

MAIN SEMINAR

Optimizing Data Usage in Neural Sequence-To-Sequence Learning

  • 8 LP
  • undergraduate, graduate

PROJECT

Research Module for MA-Students

  • 20 LP
  • graduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Summer Semester 2021

MAIN SEMINAR

Empirical Methods for NLP and Data Science

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Introduction to Neural Networks and Sequence-To-Sequence Learning

  • 8 LP
  • undergraduate, graduate

LECTURE

Mathematical Foundations

  • 6 LP
  • undergraduate

PROJECT

Software Project

  • 6+4 LP
  • undergraduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Winter Semester 2020/21

LECTURE

Statistical Methods for Computational Linguistics

  • 6 LP
  • undergraduate

MAIN SEMINAR

Deep Learning in Speech-to-Text Translation

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Imitation and Reinforcement Learning for NLP

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Oldies but Goldies

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Generalization in Deep Learning

  • 8 LP
  • undergraduate, graduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Summer Semester 2020

MAIN SEMINAR

Validity, Reliability, and Confirmation: Elementary Empirical Methods for NLP

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Grounded NLP for Spatial Navigation

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR

Introduction to Neural Networks and Sequence-To-Sequence Learning

  • 8 LP
  • undergraduate, graduate

LECTURE

Mathematical Foundations

  • 6 LP
  • undergraduate

PROJECT

Software Project

  • 6+4 LP
  • undergraduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Winter Semester 2019/20

LECTURE

Statistical Methods for Computational Linguistics

  • 6 LP
  • undergraduate

MAIN SEMINAR

Recent Advances in Sequence-To-Sequence Learning

  • 8 LP
  • undergraduate, graduate

MAIN SEMINAR (BLOCK)

Imitation Learning

  • 8 LP
  • undergraduate, graduate

Summer Semester 2019

LECTURE

Mathematical Foundations

  • 6 LP
  • undergraduate

MAIN SEMINAR

Human Reinforcement Learning

  • 8 LP
  • undergraduate, graduate

PROJECT

Software Project

  • 6+4 LP
  • undergraduate

PROJECT

Research Module for MA-Students

  • 20 LP
  • graduate

COLLOQUIUM

StatNLP Colloquium

  • (no credit points)
  • postgraduate

Bachelor and Master Theses

We offer a broad range of projects and thesis topics in Machine Learning and Natural Language Processing.

Selected Theses (2015 ~)

Bachelor

  1. One More Bridge to Cross. Bridging Natural Language to Overpass, 2022
    Supervised by Stefan Riezler and Artem Sokolov
  2. Mitigating gender bias in machine translation, 2021
    Supervised by Stefan Riezler and Michael Herweg
  3. Developing a Speech-to-Text Model that Specialises in Filler Word Detection, 2021
    Supervised by Stefan Riezler and Katja Markert
  4. Medication Extraction from Cardiology Discharge Letter, 2021
    Supervised by Stefan Riezler and Katja Markert
  5. Investigation of different Topic Modeling Frameworks and Identification of Topics and Trends in a Collection of Funding Proposals of German Federal Ministries, 2021
    Supervised by Stefan Riezler and Michael Herweg
  6. Personalized German ASR for dysarthric speech with limited data, 2021
    Supervised by Stefan Riezler and Michael Herweg
  7. Investigating the Effects of Reinforcement Learning in Neural Machine Translation, 2021
    Supervised by Stefan Riezler and Michael Herweg
  8. Quantized Neural Networks for Keyword Spotting on Neuromorphic Hardware, 2020
    Supervised by Stefan Riezler and Holger Fröning
  9. Derivative-free Optimization for Sequence-to-Sequence Models, 2020
    Supervised by Stefan Riezler and Artem Sokolov
  10. Parsing of Open Street queries with the Transformer model, 2019
    Supervised by Stefan Riezler and Artem Sokolov
  11. Cold-Start Reinforcement Learning For Neural Machine Translation, 2019
    Supervised by Stefan Riezler and Vivi Nastase
  12. Curriculum Learning für Neural Machine Translation, 2019
    Supervised by Stefan Riezler and Anette Frank
  13. Dialogue Management: Improving Task-Oriented Conversational Agents with Deep Learning, 2019
    Supervised by Stefan Riezler and Vivi Nastase
  14. Parsing NLmaps queries using Adversarial Neural Machine Translation, 2018
    Supervised by Stefan Riezler and Artem Sokolov
  15. Low Resource Translation for Middle Egyptian, 2018
    Supervised by Stefan Riezler and Ines Rehbein
  16. Anonymization of German Medical Admission Notes, 2018
    Supervised by Stefan Riezler and Vivi Nastase
  17. Deterministic Annealing for Minimum Risk Neural Machine Translation, 2018
    Supervised by Stefan Riezler and Vivi Nastase
  18. Open-Domain Semantic Parsing for Digital Assistants Using Dynamic Slot Filling, 2017
    Supervised by Stefan Riezler and Vivi Nastase
  19. Feedback-based Machine Translation with LinUCB, 2017
    Supervised by Stefan Riezler and Artem Sokolov
  20. Estimierung von Alter und Geschlecht auf Basis deutscher Textdaten aus Internetforen, 2016
    Supervised by Stefan Riezler and Anette Frank
  21. Ensemble Learning for Machine Translation Quality Estimation, 2016
    Supervised by Stefan Riezler and Artem Sokolov
  22. Multimodal Pivots for Statistical Machine Translation, 2015
    Supervised by Stefan Riezler and Artem Sokolov
  23. Informationsextraktion aus klinischen Texten, 2015
    Supervised by Stefan Riezler and Petra Knaup-Gregori

Master

  1. Chinese Shouxian Dialect to English Speech-to-Text Translation, 2022
    Supervised by Stefan Riezler and Katja Markert
  2. BERT for semantic search in customer support tickets, 2021
    Supervised by Stefan Riezler
  3. An Online Learning System for Parsing and Answering Geographical Queries in Natural Language, 2021
    Supervised by Stefan Riezler and Katja Markert
  4. Zeroth Order Optimization for Textual Adversaries, 2021
    Supervised by Stefan Riezler and Artem Sokolov
  5. Improving Date Selection in Timeline Summarization, 2020
    Supervised by Katja Markert and Stefan Riezler
  6. Towards Error-Aware Interactive Semantic Parsing, 2020
    Supervised by Stefan Riezler and Artem Sokolov
  7. Graph Based Representation and Law Prediction for German Court Decisions, 2020
    Supervised by Stefan Riezler and Michael Gertz
  8. Neural Methods for Metaphor and Metonymy Recognition, 2020
    Supervised by Katja Markert and Stefan Riezler
  9. Unsupervised Sentence Summarization using Metropolis-Hastings Algorithm, 2019
    Supervised by Katja Markert and Stefan Riezler
  10. Automatic Proficiency Scoring for Young Second Language Learners, 2019
    Supervised by Stefan Riezler and Vivi Nastase
  11. Zeroth-Order Bandit Learning for Structured Prediction, 2019
    Supervised by Stefan Riezler and Artem Sokolov
  12. Learning to Learn Competitive Neural Machine Translation Models using Evolution Strategies, 2018
    Supervised by Stefan Riezler and Katja Markert
  13. Automatische Spracherkennung in der logopädischen Diagnostik, 2017
    Supervised by Stefan Riezler and Katja Markert
  14. SAGA with Perturbations, 2017
    Supervised by Stefan Riezler and Artem Sokolov
  15. Quality Estimation and Automatic Post-Editing in a Multi-Task Learning Framework, 2017
    Supervised by Stefan Riezler and Katja Markert
  16. Quality Estimation from Scratch, 2016
    Supervised by Stefan Riezler and Artem Sokolov
  17. Statistical Machine Translation for Alignments between Images and Captions, 2016
    Supervised by Stefan Riezler and Yannick Versley
  18. Supervised Classification of Painting Descriptions, 2015
    Supervised by Stefan Riezler and Karin Haenelt