Hazhar Rahmani
Papers
8
Total Citations
32
H-Index
3
About
Hazhar Rahmani’s research lies at the intersection of robotics, formal methods, and active perception, with a focus on how robots can efficiently model, monitor, and verify their environments. His most influential work, “On the Relationship Between Bisimulation and Combinatorial Filter Reduction” (11 citations), establishes a foundational link between two key concepts in state-space compression, enabling robots to operate with reduced computational power while preserving essential information. This line of inquiry extends into integer linear programming formulations for filter partitioning and acceleration techniques for combinatorial filter reduction, addressing the NP-complete nature of exact reduction. Rahmani has also pioneered the study of narrative observation, where robots must selectively attend to and summarize unpredictable events—a problem with applications in surveillance, safety verification, and human-robot interaction. His work on sensor selection for detecting deviations from planned itineraries (4 citations) and opacity-enforcing active perception against eavesdropping attacks further demonstrates his commitment to security-aware robotics. With a growing citation record and contributions spanning both theoretical foundations and practical planning algorithms, Rahmani is shaping how robots reason about, compress, and communicate their understanding of complex, uncertain worlds.
Research Focus
Key Achievements
Top Papers
- 1On the Relationship Between Bisimulation and Combinatorial Filter Reduction11 citations · 2018
- 2
- 3Sensor selection for detecting deviations from a planned itinerary4 citations · 2021
- 4Accelerating combinatorial filter reduction through constraints3 citations · 2021
- 5
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- 7Conditioning Style on Substance: Plans for Narrative Observation2 citations · 2021
- 8