Accepted for the text mining and generation workshop of KI2022.

Hamann, F., Ulges, A., Krechel, D., & Bergmann, R. (2021, July). Open-World Knowledge Graph Completion Benchmarks for Knowledge Discovery. In International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (pp. 252-264). Springer, Cham.

N. Kurz, F. Hamann and A. Ulges, "Neural Entity Linking on Technical Service Tickets," 2020 7th Swiss Conference on Data Science (SDS), Luzern, Switzerland, 2020, pp. 35-40, doi: 10.1109/SDS49233.2020.00014.

Hamann, F., Kurz, N., & Ulges, A. (2019). Hamming Sentence Embeddings for Information Retrieval. arXiv preprint arXiv:1908.05541.

My dissertation studies how modern deep learning approaches for information retrieval can be applied to industrial use-cases. Specifically, how well neural inductive reasoning models are able to be combined with pre-trained neural text encoders.

Employing modern deep learning models for knowledge acquisition and text mining in industrial settings. Industry partners include Empolis, R+V and Volksbank Mittelhessen.

Courses: Programming 3 and Algorithms & Data Structures. Applying higher programming concepts in C and Python: Logical, functional and imperative language paradigms. Understanding, designing and implementing algorithms and data structures. Assess their runtime complexity.

Setting up and maintaining the technical infrastructure for the media computer science major. This included provisioning of all virtualized and bare-metal servers (Debian) using Salt and continuous monitoring using Grafana & Icinga. Virtualized servers were administrated using Proxmox. Switched lab computers to UEFI boot (both dual-boot and triple-boot of Linux, Windows, and OSX). Introduced a Windows domain controller and switched all lab PCs to Windows 10 (from 7).

Implemented a program in Elixir to do data cleaning on a high availability cluster (RIAK). Following that, in my bachelor's thesis, I've implemented a low-level store-and-forward messaging service in C to pass messages to RabbitMQ. Code on Github.

Cross platform development for a web app using Cordova.

Thesis: A Neural Embedding Compressor for Scalable Document Search (Code on Github, Thesis as PDF)

Thesis: Samwise - A Store and Forward Messaging Service (Code on Github)