Shaghayegh Keyumarsi
Papers
2
Total Citations
24
H-Index
1
About
Shaghayegh Keyumarsi is a rising leader in the field of safe autonomous navigation, specializing in the development of advanced control-theoretic frameworks for mobile robots operating in unknown and dynamic environments. Her primary research focuses on Control Barrier Functions (CBFs), where she has made significant contributions to overcoming fundamental limitations of traditional safety filters. In her highly cited 2023 work, "LiDAR-Based Online Control Barrier Function Synthesis for Safe Navigation in Unknown Environments" (23 citations), Keyumarsi pioneered a novel approach that enables real-time CBF construction using only onboard LiDAR data, effectively bridging the gap between theoretical safety guarantees and practical deployment in unstructured settings. Her most recent 2025 paper introduces the "Circulation-embedded Control Barrier Function," a breakthrough solution that addresses the persistent problem of undesired equilibria and dysfunctional circulation in CBF-based controllers—a critical issue that often leads to deadlocks in multi-agent and cluttered environments. By tackling these real-world safety challenges, Keyumarsi’s work is shaping the next generation of resilient, collision-free autonomous systems, making her a researcher to watch in the robotics and control systems community.
Research Focus
Key Achievements
Top Papers
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- 2