Jan Trienes
For the fall semester of 2023, I visited the University of Texas at Austin to work with Jessy Li. 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.
Education
- PhD – Computer Science, University of Marburg, Germany (03/2021 – today)
- MSc – Computer Science, University of Twente, Netherlands (2017 – 2019)
- BSc – Software Engineering, Fontys University, Netherlands (2013 – 2017)
Experience
- University of Texas at Austin, United States. Visiting scholar (fall 2023). Visiting Jessy Li at UT Austin NLP. My stay was supported through the competitive DAAD IFI scholarship.
- University of Duisburg-Essen, Germany. Research assistant (03/2021 – 04/2024). Working at the Institute for AI in Medicine (IKIM).
- Nedap Healthcare, Netherlands. Machine learning engineer (2019 – 2021).
- Nedap Healthcare, Netherlands. Graduate intern (2018 – 2019).
- University of Stavanger, Norway. Research intern (summer 2018). Visiting IAI Group led by Krisztian Balog.
- codecentric AG, Germany. Graduate intern (2017).
- Capgemini, Germany. DevOps intern (2016).
Activities
- 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), COLM (2024), ECIR (2024, 2023, 2022), EMNLP (2022).
Publications
FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence
Sebastian Joseph, Lily Chen, Jan Trienes, Hannah Louisa Göke, Monika Coers, Wei Xu, Byron C. Wallace, Junyi Jessy Li
arXiv, 2024
[pdf] [code] [data]
InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
Jan Trienes, Sebastian Joseph, Jörg Schlötterer, Christin Seifert, Kyle Lo, Wei Xu, Byron C. Wallace, Junyi Jessy Li
arXiv, 2024
[pdf] [website] [code] [data]
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
[pdf] [code] [slides]
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
[pdf] [website]
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
[pdf] [code] [slides] [poster]
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
[pdf] [code]
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
[pdf] [code] [slides]
Identifying Unclear Questions in Community Question Answering Websites
Jan Trienes, Krisztian Balog
41st European Conference on Information Retrieval (ECIR’19), 2019
[pdf] [code]
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
[pdf]