Zakieh Sadat Hashemifar

University at Buffalo, State University of New York

Papers

Total Citations

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About

Zakieh Sadat Hashemifar is a robotics researcher specializing in simultaneous localization and mapping (SLAM) and semantic mapping for long-term autonomous navigation. Her work addresses a critical challenge in robotics: enabling robots to operate reliably in dynamic, semi-static, and indoor environments where traditional SLAM assumptions fail. Her most cited paper, "Practical Persistence Reasoning in Visual SLAM" (13 citations), introduces persistence filters that allow robots to reason about temporary changes in their surroundings during repeated traversals—a key capability for service and assistive robots. She also contributed to efficient semantic mapping through "Consistent Cuboid Detection for Semantic Mapping" (10 citations), which reduces high-dimensional sensor data into compact, meaningful representations using geometric primitives. Her research on integrating WiFi signals with RGB-D SLAM demonstrates innovative approaches to improving localization robustness. With a focus on geometric mapping for sustained indoor autonomy, Hashemifar's work bridges the gap between theoretical SLAM research and practical deployment in real-world environments. Her contributions are particularly valuable for applications requiring constant movement between regions while maintaining accurate navigation and localization over extended periods.