Timo has a PhD in computer science. His background is in machine learning and software engineering and he works across both disciplines, focusing mainly on applied oriented research in the field of public safety and health.
AI Innovation Group
Biomedical AI Group
Machine Learning Group
Data Science and System Platforms Division
Multi-Modal Knowledge Graphs
- Carolin Lawrence, Timo Sztyler, and Mathias Niepert. Explaining Neural Matrix Factorization with Gradient Rollback. http://arXiv.org/abs/2010.05516. Under Review. 2020.
- Timo Sztyler, Brandon Malone. Unified Representation Learning of Biological Entities and Documents for Predicting Protein-Disease Relationships. http://biorxiv.org/content/10.1101/2020.10.27.357202v1. Under Review. 2020.
- Gabriele Civitarese, Timo Sztyler, Daniele Riboni, Claudio Bettini, and Heiner Stuckenschmidt. POLARIS: Probabilistic and ontological activity recognition in smart-homes. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2019.
- Daniele Riboni, Timo Sztyler, Gabriele Civitarese, and Heiner Stuckenschmidt. Unsupervised recognition of interleaved activities of daily living through ontological and probabilistic reasoning. International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp). 2016.
- Timo Sztyler, Heiner Stuckenschmidt. On-body localization of wearable devices: An investigation of position-aware activity recognition. IEEE International Conference on Pervasive Computing and Communications (PerCom). 2016.