Daniel Neider

**Daniel Neider** is a Professor of Security and Explainability of Learning Systems at Carl von Ossietzky University of Oldenburg. His research focuses on secure machine learning, the safety and reliability of AI systems, and their explainability. He holds a PhD in Computer Science from RWTH Aachen University (2014) and a Habilitation in theoretical computer science from TU Kaiserslautern (2022). Prior to his professorship, he was a Research Group Leader at the Max Planck Institute for Software Systems (2017–2022) and a Postdoc at RWTH Aachen and the University of Illinois at Urbana-Champaign (2014–2017).

His work bridges formal methods and machine learning, emphasizing verification of neural networks, temporal logic-based explainability, and robust reinforcement learning. Notable contributions include neuro-symbolic verification techniques, algorithms for learning temporal properties, and frameworks for secure AI deployment.

Research interests span formal verification, interpretable AI, and the theoretical foundations of machine learning. He leads projects in the Research Center ‘Trustworthy Data Science and Security’ within the Ruhr University Alliance. Recent publications address challenges in anomaly detection, temporal query processing, and ethical AI applications.