Preeti Sharma
Papers
2
Total Citations
23
H-Index
2
About
Preeti Sharma is a distinguished researcher in theoretical computer science, with a primary focus on algorithmic robotics, optimization, and combinatorial search problems. Her work centers on the analysis of evacuation and search algorithms, particularly in adversarial or uncertain environments. Sharma’s major contributions lie in pioneering the study of average-case versus worst-case tradeoffs in multi-robot evacuation scenarios. In her highly cited 2019 paper (16 citations), she introduced a novel framework for evacuating two robots from a disk under the face-to-face communication model, challenging the field’s traditional reliance on worst-case analysis. Her 2020 follow-up (7 citations) further advanced this by formulating a multi-objective optimization problem, revealing fundamental trade-offs between average and worst-case performance. These works have reshaped how researchers evaluate algorithm efficiency in distributed robotics, bridging a critical gap between theoretical guarantees and practical performance. Sharma’s research is notable for its elegant mathematical modeling and its direct implications for real-world emergency response and autonomous search-and-rescue operations. Her innovative approach has made her a leading voice in the next generation of algorithmic game theory and mobile agent computing.
Research Focus
Key Achievements
Top Papers
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