Kathrin Seßler

Kathrin Seßler

Research Assistant, PhD student

Technical University of Munich

TUM School of Social Sciences and Technology

Chair: Human-Centered Technologies for Learning

Visiting address:
Marsstraße 20-22
80335 München

Postal address:
Arcisstraße 21
80333 München

Room: 254

Office Hours: by Appointment

Tel.: +49 89 289 24328

E-Mail: kathrin.sessler@tum.de

Career development

  • 2022 – now: PhD Candidate at TU Munich, Germany
  • 2019 – 2022: M.Sc. in Computer Science at University of Tübingen, Germany
  • 2015 – 2019: B.Sc. in Computer Science at OTH Regensburg, Germany

Outreach Activities

  • 11/2023: Panel discussion at the GesellschaftsRAUM, "The digital divide: On social inequality in the digitalized society"
  • 10/2023: Panel discussion at the media days Munich, "Can AI be creative?"
  • 09/2023: Implus talk at the "LunchTalk ChatGPT" of the GWMT Annual Meeting 2023
  • 07/2023: Participation in the panel discussion at the event "Human - Machine- Interaction" in the school experiment KI@school.
  • 07/2023: Presentation of the AI-Tutor PEER at the conference of the school experiment "Prüfungskultur innovativ".
  • 06/2023: Radio interview at the children's program Kurzwelle of Radio Feierwerk on the topic "How does ChatGPT work?". Podcast available.
  • 03/2023: Introduction talk at the event "Do you still write yourself? How AI is changing our education system" at the Bayrischen Akademie der Wissenschaften. Podcast available.
  • 03/2023: Radio interview at the Campus Magazin of the BR in the episode "Does draft legislation endanger young researchers from Germany?". Podcast available.

Research Interests

  • Machine Learning / Deep Learning
  • Tabular Data Generation
  • Natural Language Processing with Transformer Models
  • Large Language Models in Education


  • Bewersdorff A., Seßler K., Baur A., Kasneci E. & Nerdel C. (2023). Assessing student errors in experimentation using artificial intelligence and large language models: A comparative study with human raters, Computers and Education: Artificial Intelligence. https://doi.org/10.1016/ j.caeai.2023.100177.
  • Seßler, K., Xiang, T., Bogenrieder, L., & Kasneci, E. (2023, August). PEER: Empowering Writing with Large Language Models. In European Conference on Technology Enhanced Learning (pp. 755-761). Cham: Springer Nature Switzerland. https://link.springer.com/chapter/10.1007/978-3-031-42682-7_73
  • Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://www.sciencedirect.com/science/article/pii/S1041608023000195
  • Borisov, V., Seßler, K., Leemann, T., Pawelczyk, M., & Kasneci, G. (2022, September). Language Models are Realistic Tabular Data Generators. In The Eleventh International Conference on Learning Representations. https://arxiv.org/abs/2210.06280
  • Borisov, V., Leemann, T., Seßler, K., Haug, J., Pawelczyk, M., & Kasneci, G. (2022). Deep neural networks and tabular data: A survey. IEEE Transactions on Neural Networks and Learning Systems. https://ieeexplore.ieee.org/abstract/document/9998482

Also, check Google Scholar for an up-to-date list.

Best Demonstration Paper Award at ECTEL 2023

Our paper "PEER: Empowering Writing with Large Language Models" received the "Best Demonstration" Award at the European Conference on Technology Enhanced Learning (ECTEL) 2023 in Aveiro, Portugal.



Scholarship at the Studienstiftung des Deutschen Volkes from 2018 to 2022