Hi there, I'm Jan Trienes, a PhD student of computer science at the University of Duisburg-Essen, supervised by Prof. Christin Seifert
My research interests include natural language processing and information retrieval. For my PhD research, I focus on text simplification for clinical notes. I am part of the Institute for Artificial Intelligence in Medicine
at the University Hospital Essen.
For the fall semester of 2023, I am visiting the University of Texas at Austin to work with Jessy Li
on factuality and analysis of medical text simplifications. Prior to my PhD, I worked as machine learning engineer at Nedap Healthcare. During my master studies at the University of Twente, I did a research internship at the University of Stavanger, visiting Prof. Krisztian Balog
- PhD – Computer Science, University of Duisburg-Essen, Germany (03/2021 – today)
- MSc – Computer Science, University of Twente, Netherlands (2017 – 2019)
- BSc – Software Engineering, Fontys University, Netherlands (2013 – 2017)
- Visiting Scholar, University of Texas at Austin, United States (fall 2023). Visiting Jessy Li at UT Austin NLP. My stay was supported through the competitive DAAD IFI scholarship.
- Machine Learning Engineer, Nedap Healthcare, Netherlands (2019 – 2021)
- Graduate Intern, Nedap Healthcare, Netherlands (2018 – 2019)
- Research Intern, University of Stavanger, Norway (summer 2018). Visiting IAI Group led by Krisztian Balog.
- Graduate Intern, codecentric AG, Germany (2017)
- DevOps Intern, Capgemini, Germany (2016)
- Participant at the Mediterranean Machine Learning Summer School (M2L). September 2022.
- Participant at the Eastern European Machine Learning Summer School (EEML). July 2021. ⭐ Best Poster Award.
- Student volunteer at EMNLP 2022.
- Programme committee: ACL (2023), EMNLP (2022), ECIR (2024, 2023, 2022).
Guidance in Radiology Report Summarization: An Empirical Evaluation and Error Analysis
Jan Trienes, Paul Youssef, Jörg Schlötterer, Christin Seifert
16th International Natural Language Generation Conference (INLG), 2023, ⭐ Nomination for Best Evaluation Award
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, Michelle Peters, Yasmin Schmitt, Jörg Schlötterer, Maurice van Keulen, Christin Seifert
ACM Computing Surveys (CSUR), 2023
Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset
Jan Trienes, Jörg Schlötterer, Hans-Ulrich Schildhaus, Christin Seifert
EMNLP Workshop on Text Simplification, Accessibility, and Readability (TSAR), 2022
Generating Synthetic Training Data for Supervised De-Identification of Electronic Health Records
Claudia A. Libbi, Jan Trienes, Dolf Trieschnigg, Christin Seifert
Future Internet, 13(5):136, 2021
Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records
Jan Trienes, Dolf Trieschnigg, Christin Seifert, Djoerd Hiemstra
1st ACM WSDM Health Search and Data Mining Workshop (HSDM’20), 2020, ⭐ Best Paper Award
Identifying Unclear Questions in Community Question Answering Websites
Jan Trienes, Krisztian Balog
41st European Conference on Information Retrieval (ECIR’19), 2019
Recommending Users: Whom to Follow on Federated Social Networks
Jan Trienes, Andrés Torres Cano, Djoerd Hiemstra
17th Dutch-Belgian Information Retrieval Workshop (DIR’18), 2018