The main focus of our group is Natural Language Processing (NLP) applied for various tasks and settings with a special emphasis on semantic processing. We teach how to build models that extract meaning from text. Students usually work in groups to create interesting experiments, demos, and applications, that use methods of machine learning, deep learning, to solve various NLP tasks. We try to design each project so that it has the potential to mature into a real application or experiment which an be presented at an international scientific conference, such as ACL, EMNLP, LREC, or the associated workshops.


  • Statistical Natural Language Processing (Spring, 2019). A course for Master’s students. Slides. The course is based on the classic textbook of Jurafsky & Martin and represents a set of topics on (mostly) pre-neural NLP.
  • Neural Natural Language Processing (Winter, 2019). A course for Master’s students. Slides. This course is focusing mostly on neural NLP models.

Master Theses

We offer our students interesting topics that allow them to work on our projects and doing real scientific work. This involves close collaboration with the research scientists and Ph.D. students of our group, but also eventually collaborators in the University of Hamburg, University of Halle, and some other our close collaborators so the students get sufficient support.

Currently enrolled master students:

  • Daniil Moskovskiy (Skoltech-MIPT)
  • Alsu Vakhitova (Skoltech)
  • Artem Vyazentsev (Skoltech)
  • Mikhail Kuimov (Skoltech-MIPT)
  • Anna Klyeva (Skoltech-MIPT)


  • Varvara Logacheva (Research Scientist), now with Huawei
  • Elena Volf (Junior Research Engineer), now with Yandex Research.
  • Sergey Ustyantsev (Research Engineer), now with BeOrg.
  • Vitaly Protasov (Master student, Skoltech-MIPT), now with AIRI. Thesis topic: Cross-lingual lexical substitution.
  • Anton Voronov (Master student, Skoltech-MIPT), now with AIRI and PhD student at MIPT. Thesis topic: Automatic dialogue censor – style transfer for texts.
  • Igor Markov (Master student, Skoltech), now with AIRI. Thesis topic: Toxic comments classification.
  • Dmitry Puzyrev (Master student, Skoltech-HSE). Thesis topic: Policy strategies for active learning in a scalable setup.
  • Lyubov Kupriyanova (Master student, Skoltech). Thesis topic: Uncertainty estimation for active learning and misclassification detection in NLP.
  • Kirill Grashenkov (Master student, Skoltech). Thesis topic: Strategies for improving the performance of machine translation models for low-resourced language pairs.
  • Anton Razzhigaev (Master student, Skoltech), now with AIRI. Thesis topic: Text-to-triple: retrieval of knowledge graph triples for question answering.
  • Artem Shelmanov (Research Scientist), now with Sberbank AI and AIRI.
  • Denis Teslenko (Master student, Ural Federal University), now with Sberbank.
  • Filip Furaev (Master student, Skoltech-GUAP). Thesis topic: Comparative question-answering dialogue system.
  • Nikita Borovkov (Master student, Skoltech-GUAP). Thesis topic: Natural language understanding of comparative questions.

Alumni prior to Skoltech

  • Ramy Aly (Research assistant, U Hamburg). Now a Ph.D. student at U Oxford. Projects related to computational lexical semantics.
  • Mohammad Dorgham (Research assistant, U Hamburg). Now with U Kaiserslautern. Projects related to graph embedding and argument mining.
  • Hauke Heller (Bachelor student, U Hamburg). Thesis topic: Comparative query suggestion.
  • Matthias Schildwächter (Master student, U Hamburg). Thesis topic: An open-domain system for retrieval and visualization of comparative arguments from text.
  • Mirco Franzek (Master student, U Hamburg). Now with Otto GmbH. Thesis topic: Comparative argument mining.
  • Fide Marten (Master student, TU Darmstadt). Thesis topic: Predicting hypernyms in contexts with JoBimText.
  • Maria Pelevina (Master student, TU Darmstadt). Now with Deutsche Bahn R&D. Thesis topic: Unsupervised word sense disambiguation with sense embeddings.
  • Pavel Romanov (Master student, BMSTU). Now with 1C Company. Thesis topic: Visualization of the graph of semantically related words.
  • Alexey Romanov (Master student, BMSTU). Now with Microsoft, completed a Ph.D. at U Lowell (USA). Thesis topic: Serelex – a system for search and visualization of semantically related words