I am an Applied Scientist at Amazon Search in Berlin. I'm interested in efficiency in NLP and search. I have recently served as an area chair for the Efficient NLP track at EMNLP 2021 and EMNLP 2022, I am a member of the ACL working group on Efficient NLP, and I'm a co-organizer of the SustaiNLP 2022 workshop on simple and efficient NLP. Before joining Amazon, I completed my PhD at UKP Lab, TU Darmstadt, where I was a member of the senior staff.

To this end, in AdapterHub, we introduce a novel framework for sharing and integrating parameter-efficient adapter modules in transformers. With AdapterDrop, we establish and improve their computational efficiency. In MultiCQA, we study the zero-shot transfer capabilities of text matching models on a massive scale with 140 source domains to question similarity and answer selection tasks.

I managed the projects QA-EduInf: Question Answering for Educational Information and SISW: Intelligent Search in the Social Web at UKP Lab, supervised four internships, six BSc/MSc theses, and taught the data analysis project class (in 2016 and 2019) as well as the text analytics research seminar (in 2017). I contributed to two multi-year project proposals that were accepted by the German research foundation DFG. Between 2008 and 2017, I worked as a freelance software developer for direct clients and medium to large advertising firms such as SYZYGY, Ogilvy, and ETECTURE. In 2011 I created the company ARULABS UG to carry out larger projects directly.