Research Assistant, Doctoral Candidate
Fraunhofer IIS - Comprehensible Artificial Intelligence
BMBF Project hKI-Chemie
Office hours: by appointment
Emanuel Slany holds a bachelor's degree in Political Science, which he obtained from the University of Bamberg in 2018. Also at the University of Bamberg, he achieved a Master's degree in Survey Statistics in 2020. His research was focused on numerical approximation of Bayesian neural networks. During his master studies, Emanuel Slany worked at Fraunhofer IIS. Afterwards, Emanuel Slany worked as a Data Scientist for HUK-Coburg. A year and a half later, he returned to the Fraunhofer IIS, where he is currently working on the Human-Centered AI project to integrate logic with numerics in order to make Bayesian multi-objective optimization methods interactive and explainable. He is also pursuing a doctoral degree in this research area at the chair of Cognitive Systems.
Research Assistant at Fraunhofer IIS - Comprehensible Artificial Intelligence
Data Scientist at HUK-Coburg
Student Research Assistant at Fraunhofer IIS - Facial Analysis Solutions and Digital Sensory Perception
M.Sc. Survey Statistics at University of Bamberg
B.A. Political Science at University of Bamberg
The Comprehensible Artificial Intelligence research group is concerned with making AI systems trustworthy, understandable, and capable of interacting with humans.
Along with this orientation, the two main research areas are currently Neuro-Symbolic Integration, i.e. the integration of logic into neural networks, and the integration of logic into numerics. The latter has the focus on multi-objective Bayesian optimization methods.
Other research interests include:
- Bayesian Deep Learning
- Inductive Logic Programming
- Hybrid Systems
- Computational Statistical Algorithms
Emanuel Slany, Yannik Ott, Stephan Scheele, Jan Paulus, Ute Schmid (2022). CAIPI in Practice: Towards Explainable Interactive Medical Image Classification. 18th International Conference on Artificial Intelligence Applications and Innovations (AIAI 2022), Springer LNCS.
18th International Conference on Artificial Intelligence Applications and Innovations AIAI 2022 - Evolutionary Computing (2022)
45th German Conference on Artificial Intelligence (2022)
KI - Künstliche Intelligenz (2022)
Yannik Ott (2022). An explanatory interactive machine learning approach for image classification in medical engineering. Bachelor Thesis, supervision by Emanuel Slany and Ute Schmid.
Oraz Serdarov (2022). Explainable Unsupervised Learning for Fraud Detection. Cooperation with HUK-Coburg, Master Thesis, supervision by Emanuel Slany and Ute Schmid.