Carl Putterman

Papers

Total Citations

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About

Carl Putterman is a researcher advancing the frontiers of interactive imitation learning, with a focus on making human-robot collaboration more efficient and intuitive. His key research areas lie at the intersection of robotics, machine learning, and human-robot interaction, particularly in developing algorithms that reduce the cognitive and operational burden on human supervisors during robot training. Putterman’s major contribution is the introduction of **LazyDAgger**, a novel framework that minimizes context switching for human teachers by strategically deciding when to intervene in a robot’s learning process. This work directly addresses a critical bottleneck in interactive imitation learning: the high cost of human corrective interventions. The flagship paper on LazyDAgger has garnered **29 citations**, underscoring its relevance and impact in the field. By enabling robots to learn more autonomously while still benefiting from selective human guidance, Putterman’s research paves the way for more practical and scalable deployment of assistive robots in real-world settings. His work is particularly notable for its focus on human-centered design, ensuring that advances in automation do not come at the expense of the human operator’s experience or efficiency.