Jonas Krumme
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About
Jonas Krumme is a researcher at the intersection of robotics, artificial intelligence, and cognitive science, with a focus on enabling robots to learn from failure and adapt in real-world, unstructured environments. His work centers on developing computational models of causal reasoning that allow robots to diagnose why a task went wrong—such as a spill during pouring—and autonomously select alternative actions to achieve desired outcomes. This approach, grounded in probabilistic actual causation, moves beyond traditional trial-and-error methods by giving machines a form of intuitive physics and error recovery akin to human problem-solving. Although his most-cited paper, "Robot pouring: identifying causes of spillage and selecting alternative action parameters using probabilistic actual causation" (2025), has garnered 1 citation to date, its conceptual novelty positions it as a foundational contribution to the emerging field of causal robotics. Krumme’s work has significant implications for assistive robots in homes, kitchens, and laboratories, where adaptability and robustness are critical. By bridging causal inference with robotic manipulation, he is helping to build a future where machines can learn from mistakes as naturally as people do.
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