Yusuf Sale, M.Sc.
PhD student, Research assistant
Office address:
Akademiestraße 7
Room 110
80799 Munich
Research Focus
I am currently working on mathematical and statistical foundations of Uncertainty Quantification and Representation in Artificial Intelligence (AI) and Machine Learning (ML). My research aims at developing reliable and trustworthy AI and ML systems capable of accounting for inherent uncertainties in their predictions, thereby providing more reliable decision-making tools across a broad range of applications.
Moreover, I am interested in generalized notions of probability, which are persuasive in representing uncertainty in ML applications. Since such theories under a generalized notion of probability require proper uncertainty quantification, I am also investigating suitable measures of uncertainty from theoretical and practical perspectives.
I am a member of the Konrad Zuse School of Excellence in Reliable AI (relAI), sponsored by the Federal Ministry of Education and Research.
Teaching Activities
SoSe 2023
- Preference Learning and Ranking (Übung)
WiSe 2022/2023
SoSe 2022
- Stochastik und Statistik (Übung)
Thesis
- Sale, Yusuf (2022)
G-Framework in statistics. Nonlinear expectations for decision-making under uncertainty
Master Thesis (full text available)