Leonard Pleiss
Leonard Pleiss is a Roland Berger Fellow and PhD student in machine learning. His research in reinforcement learning and large language models is driven by a vision to create highly capable autonomous agents. He tackles this goal by engineering immediate algorithmic refinements that improve current learning systems, and by building robust evaluation frameworks that deepen our fundamental understanding to pave the way for more advanced, reliable agents.