معرفی
Frederik Stalschus is a doctoral researcher and full-time academic affiliated with the Technical University of Berlin and the Berlin Institute for the Foundations of Learning and Data (BIFOLD). Since 2025, he has pursued his PhD in the Machine Learning Group under the supervision of Shinichi Nakajima, focusing on Bayesian learning and uncertainty-driven optimization for real-world applications.
- Education: M.Sc. in Information Systems (2025), TU Berlin
- Industry Experience: Adaptive multi-model reinforcement learning at IBM, cloud engineering observability at SAP
His research interests include Bayesian learning, uncertainty estimation, and probabilistic machine learning, with a specific emphasis on enhancing Bayesian optimization techniques through uncertainty modeling. His work bridges theoretical advancements with practical implementations in data science and cloud systems.
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