Software Methodologies for Distributed Systems

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  8. Fabian Stieler

Fabian Stieler M.Sc.

Research Assistant
Software Methodologies for Distributed Systems
Phone: +49 821 598-2471
Email: fabian.stieler@informatik.uni-augsburg.de
Room: 3005 (N)
Visiting hours: by arrangement
Address: Universitätsstraße 6a, 86159 Augsburg

Short Curriculum Vitae

  • 2017: Bachelor of Science, Wirtschaftsinformatik
  • 2019: Master of Science, Informatik & Informationswirtschaft

Fields of Research

  • Machine Learning Operations (MLOps)
  • Explainable Artificial Intelligence (XAI)
  • Active Learning (AL)

Mentored Theses

  • Reduction of Annotation Effort - A Comparison of Active Learning Frameworks (Bachelorthesis), Original Title: "Reduktion des Annotationsaufwands - Ein Vergleich von Active Learning Frameworks"
  • Bias Detection using Interpretable Machine Learning Methods (Bachelorthesis)
  • Evaluating Explainability in the Context of Active Learning (Masterthesis)
  • Interpretable Machine Learning with ECG Data (Bachelorthesis), Original Title: "Interpretierbares Maschinelles Lernen mit EKG Daten"
  • Model Explanations as Quality Gate in Machine Learning Pipelines (Masterthesis)

Projects

Publications

2023

Fabian Stieler and Bernhard Bauer. 2023. Git workflow for active learning - a development methodology proposal for data-centric AI projects. In Hermann Kaindl, Mike Mannion and Leszek Maciaszek (Ed.). Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2023), April 24-25, 2023, in Prague, Czech Republic. SciTePress, Setúbal, 202-213 DOI: 10.5220/0011988400003464
PDF | BibTeX | RIS | DOI

 

Miriam Elia, Tobias Peter, Fabian Stieler, Bernhard Bauer, Sandra Nagl, Alanna Ebigbo and Vivien Grünherz. in press. Precision medicine for achalasia diagnosis: a multi-modal and interdisciplinary approach for training data generation [Abstract]. In IEEE - ISBI 2023: International Symposium on Biomedical Imaging, Cartagena de Indias, Colombia, April 18-21, 2023. IEEE, Piscataway, NJ
PDF | BibTeX | RIS | URL

 

2022

Fabian Stieler, Marius Nann and Bernhard Bauer. 2022. Vertrauenswürdige KI in der Medizin - von effizienter Datenannotation bis intuitiver Modellerklärung. In KI-Fabrigk @WIKOIN22, Ingolstadt, 30. Juni 2022.
BibTeX | RIS

 

2021

Fabian Stieler, Fabian Rabe and Bernhard Bauer. 2021. Towards domain-specific explainable AI: model interpretation of a skin image classifier using a human approach. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2021, 19-25 June 2021, Nashville, TN, USA. IEEE, Piscataway, NJ, 1802-1809 DOI: 10.1109/CVPRW53098.2021.00199
PDF | BibTeX | RIS | DOI

 

2020

Fabian Stieler, Fabian Rabe and Bernhard Bauer. 2020. Federated medical data - how much can deep learning models benefit? [Poster]. In AMIA 2020 Virtual Clinical Informatics Converence, May 19-21.
PDF | BibTeX | RIS

 

2018

Harald Schmidbauer, Angi Rösch and Fabian Stieler. 2018. Patterns of interest in industrial brands: Instagram media uploads and sentiment. In Len Tashman and Fotios Petropoulos (Ed.). International Symposium on Forecasting (ISF) 2018, Boulder (CO), USA, June 16-20, 2018. International Institute of Forecasters
PDF | BibTeX | RIS | URL

 

 

Harald Schmidbauer, Angi Rösch and Fabian Stieler. 2018. The 2016 US presidential election and media on Instagram: who was in the lead?. Computers in Human Behavior 81, 148-160. DOI: 10.1016/j.chb.2017.11.021
PDF | BibTeX | RIS | DOI

 

2017

Harald Schmidbauer, Angi Rösch and Fabian Stieler. 2017. Patterns of interest in industrial brands: media uploads to Instagram. In 23rd IIF Workshop on Predictive Analytics and Forecasting (IIF 2017) - Research and Applications, Munich, Germany, September 14-15, 2017. International Institute of Forecasters
BibTeX | RIS

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