M.Sc. Applied Computer Science, Heidelberg University
Python, PyTorch, Huggingface Transformers
I am a third-year PhD student, part of the Database Systems Research Group at Heidelberg University, supervised by Prof. Dr. Michael Gertz. The main focus of my PhD work lies at the intersection of Natural Language Processing (NLP) and Information Retrieval (IR); specifically, I investigate how large document collections can be made more accessible and explorable to users. This includes focused summarization systems, specifically for German, with a focus on collection-specific aspects. I have several years of experience developing Machine Learning systems in Python, and have worked with several Machine Learning frameworks, most notably PyTorch and Huggingface Transformers. If you want to know more about me, consider also checking out my full CV, or reach out to me directly via Twitter or E-mail!
I previously did my Undergraduate and Master's degree in the Applied Computer Science program at Heidelberg University. During my studies, I have also completed an exchange year in the Computer Science program at the University of Toronto.
Professionally, my interests mainly focus around Natural Language Processing and Machine Learning, with a special focus on Document Summarization, Keyphrase Extraction and Search. I spent four months during 2021 as an Applied Scientist intern at Amazon Berlin, under the supervision of Dr. Omar Zaidan, where I investigated different ways in which customer search interactions can be predicted by neural language models.
Between September 2019 and January 2021, I was employed as a part-time software engineer for the startup Codefy, where I helped to build a search platform for legal professionals in Germany. I have also previously interned at SAP SE in Walldorf, working on optimizations for Machine Learning operators in automated pipelines.
Most of my other professional experience is in teaching, as I have held several positions as a Teaching/Lecture Assistant during my time at Heidelberg University. I am fortunate enough that I can continue teaching during my PhD, where I additionally supervise student projects and theses. At our chair, we put special focus on teaching students real-world skills, which includes regular code reviews, as well as large group projects. If you are interested in collaborating with me, or discussing ideas, please reach out to me!.
Related to teaching, I also spend a lot of my free time answering questions on Stackoverflow, where I rank highly in several ML-related tags, and have been in the top 5% of users every year since 2018. Previous side projects include medical text extraction at Metaplx, a project that aims to utilize recurrent neural networks to automatically extract clinical data from scholarly articles, which can greatly reduce the overhead for medical professionals at all levels. For more of my smaller projects, you can also check out my personal GitHub.
For now, a list of already published research papers is available on my Google Scholar Page. A full list of manuscripts, including preprints and unpublished results, can be found on my university homepage.