Michael Fishman
Papers
2
Total Citations
86
H-Index
2
About
Michael Fishman is a leading researcher in human-robot interaction and autonomous decision-making under uncertainty, with a focus on mixed reality interfaces and object-oriented planning. His most cited work, "Mixed Reality as a Bidirectional Communication Interface for Human-Robot Interaction" (2020, 49 citations), introduces a decision-theoretic model that enables robots to interpret multimodal human communication—such as speech and gestures—and resolve ambiguities through a mixed reality interface, bridging physical and virtual behaviors for more intuitive collaboration. In "Multi-Object Search using Object-Oriented POMDPs" (2019, 37 citations), Fishman addresses the computational challenges of Partially Observable Markov Decision Processes (POMDPs) in large-scale domains, proposing an object-oriented framework that allows robots to efficiently reason about multiple objects under uncertainty—a critical capability for real-world tasks like search and rescue or warehouse automation. His work has been recognized for advancing practical, scalable AI in robotics, with applications spanning assistive technologies and autonomous systems. Fishman’s contributions have garnered significant attention, earning him a reputation for bridging theoretical rigor with deployable solutions in human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multi-Object Search using Object-Oriented POMDPs37 citations · 2019