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Information Systems and Applied Computer Sciences

Chair of Explainable Machine Learning

  1.  University of bamberg
  2. Faculties
  3. Information Systems and Applied Computer Sciences
  4. Subject groups
  5. Applied Computer Science
  6. Chair of Explainable Machine Learning
  7. Team
  8. Jonas Alle, M.Sc.

Jonas Alle

Teaching and Research Assistant

M.Sc., Doctoral Candidate

Anschrift:      An der Weberei 5, 96047 Bamberg
Raum:            WE5/04.090

Since 2024                                       PhD Candidate at the xAI Lab of the Otto-Friedrich University Bamberg, Germany 
2023Probabilistic Numerics Spring School, three day school and research workshop, Eberhard Karls Universit?t, Tübingen, Germany 
2023Machine Learning for Good (ML4G), ten day AI safety bootcamp, Paris, France 
2019 - 2023Master of Science in Computational Engineering, Friedrich-Alexander-Universit?t Erlangen-Nürnberg, Germany 
2018 - 2023Student Research Assistant, Development of deep neural networks for segmentation tasks on reconstructed CT-volumes, Fraunhofer IIS, Germany 
2015 - 2019Bachelor of Science in Applied Mathematics and Physics, Technische Hochschule Georg-Simon-Ohm, Nürnberg, Germany 

 

Main Research Interests

  • Faithful and robust uncertainty estimation with Bayesian Neural Networks
  • Probability distributions in input-, output-, embedding-, and parameter space
  • Theoretical investigations of information flow through deep neural networks
  • Mathematical exploration of Random Neural Networks
  • Research in embedding space geometry, topology, and related characteristics
  • Finding theoretical, mathematically founded, guarantees for deep learning models
  • Insightful data visualization

 

  • Alle J.: Uncertainty Estimation for Instance Segmentation of Large-Scale CT Data with Flood-Filling Networks. Master's Thesis, Friedrich-Alexander University Erlangen-Nuremberg. 2023. (unpublished)
  • 3D Segmentation of Plant Root Systems using Spatial Pyramid Pooling and Locally Adaptive Field-of-View Inference: Alle,J., Gruber,R., W?rlein,N., Uhlmann,N., Clau?en,J., Wittenberg,T., Gerth,S.; Frontiers in Plant Science, vol. 14, (2023), https://doi.org/10.3389/fpls.2023.1120189

Thesis Supervision

Please check out our official bidding for thesis topics [Link to VC-Course] or contact me directly via email to request supervision of your Bachelor’s or Master’s Thesis.

WS24/25

  • xAI-Proj-B: Bachelor Project Explainable Machine Learning
  • xAI-DL-M: Deep Learning Exercise