Juraj Vladika

staff sebis nlp deep learning

School of Computation, Information and Technology
Department of Computer Science
Chair of Software Engineering for Business Information
Systems (sebis), I19

Technical University of Munich
Boltzmannstraße 3
85748 Garching, Germany

juraj.vladika [at] tum.de

Room FMI 01.12.057

Office hours: by appointment

I offer guided research or thesis supervision for motivated students in research areas listed below. If you would like to propose a topic related to my research interests or get in touch to find a suitable one, please send me an e-mail with your CV and transcript of records attached.

Curriculum Vitae

Juraj Vladika has been a research associate at the chair for Software Engineering of Business Information Systems at the Technical University of Munich since January 2022. He holds a bachelor's and a master's degree in Computer Science from the University of Zagreb.

During his studies, he spent a semester abroad at the Technical University of Vienna and a semester at the Pontificial University Comillas in Madrid. Before joining sebis, he gained work experience as a student researcher and a teaching assistant at the Faculty of Electrical Engineering and Computing in Zagreb and in data science internships in the industry.

Research Interests

Natural Language Processing
Information Retrieval
Automated Fact-Checking & Claim Verification
Question Answering
Natural Language Reasoning
Knowledge Graphs
Legal Tech & Responsible AI

Research Projects

VeriSci – Scientific Claim Verification with Evidence from Text and Structured Knowledge

The research project VeriSci aims to develop NLP solutions for the task of automated fact verification of scientific claims. This process includes claim detection, evidence retrieval from documents and structured knowledge sources, reasoning over the evidence, and claim veracity assessment. The project will investigate and evaluate state-of-the-art approaches for this problem and explore other related tasks of natural language understanding for the scientific domain. Read more

NLawP – Natural Language Processing and Legal Tech

The project NLawP evaluates how AI technologies can impact the legal sector in disruptive ways. NLawP will map state of the art applications and what we currently know about their implications concerning responsible AI. It will also look into the next steps concerning a sustainable data infrastructure for the legal sector. Furthermore, the project will inquire into potential innovations and imaginaries of stakeholders. A multi-perspective methodology will allow to research this emerging field of AI with a view to innovation, adoption, responsible uses, and infrastructures. Read more

Teaching (in reverse chronological order)

Term	Level	Title	Type	Role
WS 23/24	Bachelor	Software Engineering for Business Applications - Bachelor's Course (SEBA Bachelor)	Lecture	Organizer
WS 23/24	Master	SEBA Lab Course	Lab Course	Advisor
SS 23	Master	Natural Language Processing - Methods and Applications	Seminar	Advisor
SS 23	Master	SEBA Lab Course (NLP): Conversational Agents	Lab Course	Advisor
SS 23	Master	Software Engineering for Business Applications (SEBA Master)	Lecture	Advisor
WS 22/23	Bachelor	Software Engineering for Business Applications - Bachelor's Course (SEBA Bachelor)	Lecture	Organizer
WS 22/23	Master	SEBA Lab Course	Lab Course	Advisor
SS 22	Master	Natural Language Processing - Methods and Applications	Seminar	Advisor
SS 22	Master / Bachelor	Conversational AI Workshop	Certificate Course	Organizer
SS 22	Master	Software Engineering for Business Applications (SEBA Master)	Lab Course	Advisor

Publications (in reverse chronological order)

2024
[Link]	Vladika, J.; Matthes, F. Comparing Knowledge Sources for Open-Domain Scientific Claim Verification. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics 2024 (EACL 2024), pages 130-138, St. Julian's, Malta. Association for Computational Linguistics.
[Link]	Vladika, J.; Fichtl, A. and Matthes, F.. Diversifying Knowledge Enhancement of Biomedical Language Models Using Adapter Modules and Knowledge Graphs. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 2 (ICAART 2024), ISBN 978-989-758-680-4, ISSN 2184-433X, pages 376-387.
2023
[Link]	Vladika, J.; Matthes, F. Scientific Fact-Checking: A Survey of Resources and Approaches. In Findings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada. Association for Computational Linguistics.
[Link]	Vladika, J.; Matthes, F. Sebis at SemEval-2023 Task 7: A Joint System for Natural Language Inference and Evidence Retrieval from Clinical Trial Reports. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), Toronto, Canada. Association for Computational Linguistics.
[Link]	Schneider, P.; Afzal, A.; Vladika, J.; Braun, D.; Matthes, F. Investigating Conversational Search Behavior For Domain Exploration. In European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland. Springer.
[Link]	Afzal, A.; Vladika, J.; Braun, D.; Matthes, F. Challenges in Domain-Specific Abstractive Summarization and How to Overcome Them. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence (ICAART 2023), Lisbon, Portugal. SCITEPRESS - Science and Technology Publications.
2022
[Link]	Schneider, P.; Schopf, T.; Vladika, J.; Galkin, M.; Simperl, E.; Matthes, F. A Decade of Knowledge Graphs in Natural Language Processing: A Survey. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP 2022), Taipei, Taiwan (Online). Association for Computational Linguistics.
[Link]	Vladika, J.; Meisenbacher, S.; Matthes, F. 2022. TUM sebis at GermEval 2022: A Hybrid Model Leveraging Gaussian Processes and Fine-Tuned XLM-RoBERTa for German Text Complexity Analysis. In Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text (KONVENS 2022), pages 51–56, Potsdam, Germany. Association for Computational Linguistics.
2019
[Link]	Palić, N.; Vladika, J.; Čubelić, D.; Lovrenčić, I.; Buljan, M.; Šnajder, J. TakeLab at SemEval-2019 Task 4: Hyperpartisan News Detection. In Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2019), pages 995–998, Minneapolis, Minnesota, USA. Association for Computational Linguistics.