Research Group

Human Language Technologies

Prof. Dr. Ivan Habernal
Professor of Natural Language Processing
at Paderborn University

Welcome to my official research website!
logo PB


TrustHLT Group

Trustworthy Human Language Technologies (TrustHLT) is a research group associated with the Professorship for Natural Language Processing at Paderborn University and led by Ivan Habernal. TrustHLT started in 2021 as an independent research group at the Technical University of Darmstadt, where some of the group members are affiliated.

Prof. Dr. Ivan Habernal

Head of the group

I hold a W2 Professorship for Natural Language Processing at Paderborn University, Germany. My current research areas include privacy-preserving NLP, legal NLP, and explainable and trustworthy models. My research track spans argument mining and computational argumentation, crowdsourcing, large-scale corpora, serious games, sentiment and sarcasm on social media, and semantic web.

Download my academic CV

Doctoral candidates and postdocs

Lena Held, MSc.

Ph.D. student

Lena is currently exploring the research area of computational argumentation in the legal domain.

Dr. Timour Igamberdiev

Postdoctoral researcher

Timour's current research areas include privacy-preserving NLP, differential privacy in graph neural networks, and privacy-preserving semantic representations of language.

Sebastian Ochs, MSc.

Ph.D. student

Sebastian' research areas include privacy-preserving NLP with a focus on text rewriting with provable guarantees.

Mahammad Namazov, MSc.

Ph.D. student

Mahammad explores interpretability in NLP applications focusing on the legal domain.

Qiankun Zheng, MSc.

Ph.D. student

Qiankun's current research areas include multimodal learning and fact-checking.

Dr. Erion Çano

Postdoctoral researcher

Erion's research is on privacy-preserving NLP and robust anonymization.

Master and Bachelor students

Jesper Schlegel

Master student

Jesper's thesis aims to detect prompt injection attacks on large language models using saliency methods.


Martin Kerscher

2023, Master thesis

Martin's thesis compared privacy-preserving inference methods, applying them to NLP tasks and developing software to connect PyTorch with techniques like homomorphic encryption and garbled circuits.

Marius Büttner

2023, Master thesis

Marius investigated question answering in the German legal domain. His thesis explored how well existing models can support laymen to receive a first legal aid, based on a created dataset of questions in lay language to answers in legalese. → EACL'24 paper

Christopher Weiss

2023, Master thesis

Chris's thesis focused on finding best practices on how to optimally adapt the concept of differential privacy in NLP environments while putting the needs of the end-users first and considering perceptional biases to make differential privacy more accessible. → LREC-COLING'24 paper

Lijie Hu

2022, Research internship

Lijie is a second-year PhD student in Computer Science at King Abdullah University of Science and Technology. Her research interests cover machine learning algorithm on Explainable AI (XAI), Differential Privacy, and Differential Private Natural Language Models. She is also interested in Machine Unlearning, and other security issues in data field. → EACL'24 paper

Sudarshan Sivakumar

2022, Research internship

Sudarshan is an undergraduate student in Computer Science from India. His primary research interest is in creating language processing tools that are socially and ethically responsible. He is working on a research project related to differentially private synthetic data generation.

Nina Mouhammad

2022, Master thesis

Nina wrote her thesis on privacy-preserving techniques for crowdsourcing sensitive text data. → Linguistic Annotation Workshop (ACL'23) paper

Johanna Frenz

2022, Bachelor thesis

Johanna studied computer science at TU Darmstadt. In her bachelor thesis, she compiled an easily accessible legal benchmark dataset to enable evaluating models on a variety of legal NLP tasks.

Lars Wolf

2022, Master thesis

Lars, student of information systems technologies, cooperated with political scientists to identify indoctrination in German history textbooks through entity emotion analysis.

Ying Yin

2022, Master thesis

Ying explored privacy-preserving transformer models in the legal domain. Her thesis combined large-scale pre-training with differential privacy and evaluates the trade-off between privacy-preserving capability and downstream performance. → Legal NLP workshop (EMNLP'22) paper

Sarah Lettmann

2021, Master thesis

Sarah explored ethical argumentation in scientific literature. Her thesis focused on controversial technologies and automatic mining of absent, shifting, and evolving ethical arguments.

Manuel Senge

2021, Bachelor thesis

Manuel was a bachelor's student at the TU Darmstadt focusing on machine learning. He wrote his thesis on the effectiveness and impact on accuracy using differential privacy in NLP. → EMNLP'22 paper

Lena Held

2021, Master thesis

Lena studied computer science at TU Darmstadt. In her thesis she dealt with differentially private language representation learning.

Daniel Faber

2021, Master thesis

Daniel explored legal argument mining in court decisions with focus on ECHR decisions and their art of argumentation in regard to their importance level. → AI & Law journal paper

Fabian Kaiser, M.Sc.

2020-2021, TU Darmstadt research Scholarship

Fabian's research area included legal argument mining, expert annotations, and low-resource and few-shot transfer learning for annotation recommendations.


Open positions

There are currently no open positions



March, 2024

Paper accepted at LREC-COLING

LREC-COLING 2024, the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation accepts one long paper by Chris Weiss, Frauke Kreuter (LMU Münchnen) and Ivan Habernal on user perception of privacy guarantees in NLP datasets.

January, 2024

Three papers accepted at EACL

The 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024) accepts one long paper by Marius Büttner and Ivan Habernal (main conference) entitled "Answering legal questions from laymen in German civil law system", one demo-paper by Timour Igamberdiev, Doan Nam Long Vu, Felix Künnecke, Zhuo Yu, Jannik Holmer, and Ivan Habernal entitled "DP-NMT: Scalable Differentially-Private Machine Translation", and one EACL Findings paper by Lijie Hu et al., co-authored by Ivan Habernal, entitled "Differentially Private Natural Language Models: Recent Advances and Future Directions".

November, 2023

Annual Conference of efl

I'm giving an invited talk at the 2023 Annual Conference of efl – the Data Science Institute in Frankfurt am Main.

October, 2023

W2-Professorship in Paderborn

I'm starting a new position as W2 Professor of Natural Language Processing at Paderborn university.

September 20, 2023

Keynote Talk at TSD 2023

The Text, Speech and Dialogue (TSD 2023) conference invited me to the beautiful city of Pilsen, Czech Republic, to give a keynote talk on privacy in NLP.

July 20, 2023

Timour Igamberdiev defended his PhD thesis

Timour Igamberdiev successfully defended his dissertation thesis on Differential Privacy in NLP with magna cum laude grade. Timour is the first PhD student graduating from the TrustHLT group!

May 10, 2023

Two papers accepted to ACL Findings

TrustHLT has two papers on privacy-preserving NLP accepted to the Findings of the Association for Computational Linguistics: ACL 2023, co-authored by Timour Igamberdiev, Cleo Matzken, and Steffen Eger.

May 6, 2023

Tutorial on Private NLP at EACL

We held a tutorial on Privacy-Preserving Natural Language Processing at the The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023) in Dubrovin, Croatia. The slides are available at GitHub.

March 15, 2023

Invited talk at Aalto University

It was my pleasure to give an invited talk about Privacy-Preserving Natural Language Processing at the Aalto University in Helsinki. The video recording should soon become available.

March 1, 2023

Tutorial accepted at EACL

The 17th Conference of the European Chapter of the Association for Computational Linguistics will host our tutorial on Privacy-Preserving Natural Langauge Processing in Dubrovnik, in May 2023.

October 7, 2022

Paper accepted at EMNLP

Our new paper "One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks" by Manuel Senge, Timour Igamberdiev, and myself will be presented at the 2022 Conference on Empirical Methods in Natural Language Processing in Abu Dhabi in December this year.

October 1, 2022

Interim Professorship at LMU

In this winter term, I'm holding a W2 interim professorship at the The Center for Information and Language Processing at the Ludwig-Maximilians-Universität München.

August 17, 2022

Paper accepted at COLING

Our new paper "DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting" by Timour Igamberdiev (TrustHLT), Thomas Arnold (UKP), and myself will be presented at the 29th International Conference on Computational Linguistics in Korea in October this year.

August 2, 2022

Member of hessian.AI

I'm now a member of hessian.AI — The Hessian Center for Artificial Intelligence. Its mission is to drive research excellence, education, practice and leadership in AI to foster economic growth and improve the human condition.

April 5, 2022

Paper accepted at LREC

Our paper on protecting privacy of models trained on graph data using differential privacy has been accepted at the International Conference on Language Resources and Evaluation (LREC) to be held in Marseille, France in June.

February 24, 2022

Paper accepted at ACL

Our paper analyzing trickiness of differentially-private text representation learning will be presented at the 60th Annual Meeting of the Association for Computational Linguistics, the world's top conference for natural language processing.

October 21, 2021

Invited lecture at University of Maine

I'm giving an invited lecture at the School of Computing and Information Science, University of Maine with a bit provoking title "If all you have is a hammer, everything looks like a nail: SGD-DP in privacy-preserving NLP" (download slides).

September 1, 2021

Paper accepted at EMNLP

Our paper on the pitfalls of differential privacy in NLP will be presented at the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), one of the world's leading conferences for natural language processing.

June 10, 2021

Guest lecture on "AI and Criminal Justice"

I'll be giving a guest lecture at the International Summer School on "AI and Criminal Justice" in Rome on July 12th. This summer school is a great opportunity to acquire an interdisciplinary and in-depth knowledge in the cutting-edge area of AI and criminal justice.

April 19, 2021

Hosting mentoring session at EACL

I'm happy to volunteer as a mentor for early career researchers at this year's Conference of the European Chapter of the Association for Computational Linguistics (EACL). One of the topics on the agenda is "How to survive grad school", I'm very much looking forward to some fresh perspectives!

March 17, 2021

Invited talk on privacy-preserving NLP

Thanks to Yang Gao for invited me over to Royal Holloway, University of London to give an invited talk on privacy-preserving NLP, a joint work with Timour Igamberdiev. Slides available here.

March 3, 2021

Area Chair for argument mining at EMNLP

Happy to join the Area Chairs for sentiment analysis and argument mining at this year's Conference on Empirical Methods in Natural Language Processing (EMNLP).

January 14, 2021

Serving as Area Chair for *SEM 2021

I'll be serving as Area Chair ("Semantics for NLP Applications") at the upcoming *SEM conference, which is co-located with ACL'21 in Thailand this year.

December 27, 2020

Standing reviewer of Computational Linguistics

I happily accepted an invitation to join the standing reviewer board of Computational Linguistics, the "longest-running publication devoted exclusively to the computational and mathematical properties of language".

May 21, 2020

Serving as Tutorial Chair for EACL 2021

Together with Isabelle Augenstein and tutorial chairs for NAACL, EMNLP, and ACL-IJCNLP, we are preparing the next year's selection of tutorials to be presented either virtually or in-person.


Selected publications

For the complete list, see my Google Scholar profile.

0 H-index
0 Citations
33 ACL-Anthology papers
6 Journals + book chapters


Research projects


Empirical Computational Argumentation in Legal Proceedings

Funded by the DFG

In this interdisciplinary collaboration, we look into argumentation in the verdicts of the European Court of Human Rights. What makes a verdict of a high importance? Is it the facts? Is it the argumentation pattern? Is it the judges? Or is it something left between the lines?

We combine legal expertise with state-of-the-art NLP.

We collaborate with expert legal researchers Prof. Dr. Christoph Burchard from Geothe University Frankfurt.

logo logo
Prof. Dr. Christoph Burchard, LL.M. (NYU)
Prof. Dr. Christoph Burchard, LL.M. (NYU)
Goethe Universität Frankfurt am Main

Chair for German, European and International Criminal Law and Procedure, Comparative Law and Legal Theory


Truly Privacy-Preserving Machine Translation

Funded by the HMdIS

What does is mean for machine translation models to protect privacy? What personal information do neural machine translation systems leak? Can we protect users during inference?

In this research project supported by the Hessisches Ministerium des Innern und für Sport we tackle privacy-preserving natural language processing in the context of machine translation, including differential privacy and cryptographical tools.

ATHENE SenPai Text

Protecting Privacy and Sensitive Information in Texts

Funded by ATHENE

The goal of this project is to explore Natural Language Processing methods that can dynamically identify and obfuscate sensitive information in texts, with a focus on implicit attributes, for example, their ethnic background, income range, or personality traits. These methods will help to preserve the privacy of all individuals - both authors and other persons mentioned in the text. Further, we go beyond specific text sources, like social media, and aim to develop robust and highly adaptable methods that can generalize across domains and registers.

We collaborate with the UKP Lab led by Prof. Dr. Iryna Gurevych.

Prof. Dr. Iryna Gurevych
Prof. Dr. Iryna Gurevych
Technische Universität Darmstadt

Director of the Ubiquitous Knowledge Processing (UKP) Lab



Winter Term 2023/2024

Natural Language Processing with Deep Learning

Slides are freely available at GitHub under open licences.

Recorded lectures are in a YouTube playlist.

Official evaluation of my courses

I like transparency, so here are the official evaluation sheets of my courses (names of 3rd persons were redacted).



Send me an e-mail


Prof. Dr. Ivan Habernal
Department of Computer Science, Paderborn University
Fürstenallee 11, 33102 Paderborn, Germany

Email Address

ivan (dot) habernal (at)


Follow me on Twitter


Follow me on LinkedIn