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Junior Research Groups

JRG Ethics of AI

Benjamin Lange and his team conduct research into fundamental and application-related ethical issues relating to AI and ML.

They deal with fundamental and practical questions of AI ethics from a philosophical-analytical perspective.By organizing conferences, workshops and panel discussions, the group aims to enter into an interdisciplinary exchange with researchers from philosophy and other disciplines. An important focus here is also communication with the wider public about the moral and social aspects of AI.

Another important task of the JRG is the transfer of philosophical-ethical findings and results into practice, for example through collaborations and dialogue with industry and society.

Members

Link to Ben Lange

Ben Lange

Dr.

JRG Leader Ethics of AI

Link to Anna-Maria Brandtner

Anna-Maria Brandtner

JRG Ethics of AI

Link to Jesse de Jesus de Pinho Pinhal

Jesse de Jesus de Pinho Pinhal

JRG Ethics of AI

JRG Human-Centered NLP

Michael Hedderich and his team's research covers the intersection of machine learning, natural language processing (NLP) and human-computer interaction.

Human factors have a crucial interplay with modern AI and NLP development, from the way data is obtained, e.g. in low-resource scenarios, to the need to understand and control models, e.g. through global explainability methods. AI technology also does not exist in a vacuum but must be validated together with the application experts and stakeholders it should serve.

The group explores these questions from different perspectives, taking the lense of machine learning, natural language processing and human-computer interaction. By embracing these diverse perspectives, the researcher value how each viewpoint enriches the understanding of the same issues and how different skill sets complement one another.

Members

Link to Michael Hedderich

Michael Hedderich

Dr.

JRG Leader Human-Centered NLP

Link to Florian Eichin

Florian Eichin

JRG Human-Centered NLP

JRG Multi-Modal Learning

Almut Sophia Koepke and her team conduct research into multi-modal learning from vision, sound, and text.

They focus on advancing video understanding, with an emphasis on capturing temporal dynamics and cross-modal relationships. To achieve this, they aim to improve the combination of information from various modalities within learning frameworks. Furthermore, they are exploring how to adapt large pre-trained models for audio-visual understanding tasks.

Members

Link to Almut Sophia Koepke

Almut Sophia Koepke

Dr.

JRG Leader Multi-Modal Learning

Link to Daniil Zverev

Daniil Zverev

JRG Multi-Modal Learning