Oliver Wardas

Last modified Dec 8, 2023

staff person mitarbeiter sebis nlp team people legaltech

Faculty of Informatics
Chair of Informatics 19
Software Engineering for Business Information Systems (sebis)

Technische Universität München
Boltzmannstraße 3
85748 Garching bei München, Germany

Phone:	+49 89 289 17142
Fax:	-
Email:	oliver.wardas@tum.de

Room FMI 01.12.059

Office hours: by appointment

Student offers:

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

Mr. Wardas joined the chair of Software Engineering for Business Information Systems at the Technical University of Munich in November 2022. He holds a bachelor's and master's degree in Computer Science from RWTH Aachen and wrote his master thesis on the explainability of Deep Learning models for DGA detection. During his studies he also gained work experience as a Research/Student Assistant at Utimaco and RWTH Aachen. Additonally, he volunteered as an Academic Mentor and served as a Core Member in the RWTH Aachen Google Developer Student Club.

Research Interests

Natural Language Processing
Large Language Models & RAG
Legal Tech

Research Projects

NLawP – Natural Language Processing and Legal Tech

The project NLawP evaluates how AI technologies can impact the legal sector in disruptive ways. It will map current developments in research and in the legal tech market, inquire into how data governance can enable a responsible and efficient adoption, and bring stakeholders together in order to produce new ideas and innovations. 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.
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