Papers
27
Total Citations
263
H-Index
11
About
Yara Khaluf is a leading researcher in swarm robotics and collective intelligence, whose work bridges theoretical modeling and real-world applications. Her primary contributions lie in understanding how decentralized systems—from robot swarms to social insects—achieve coherent collective behavior through local interactions and noise. She has pioneered task allocation strategies for time-constrained problems, notably with her "Local ant system" (26 citations) and foundational work on soft deadlines (13 citations), which directly impact the efficiency of distributed robotic systems. Khaluf’s research also explores biologically inspired models, such as collective Lévy walks for exploration (13 citations) and scale-free interaction networks for adaptive foraging (12 citations), demonstrating how nature-inspired algorithms can optimize swarm performance. Her 2019 paper on coherent collective behavior (32 citations) is a standout, revealing how social feedback and noise balance to produce robust group decisions. Beyond theory, Khaluf applies her expertise to socially impactful domains, including a pro-active social robot intervention for dementia patients (16 citations). With over 150 citations across her top works, she is recognized for advancing both the mathematical foundations—using birth-death processes to model swarms (14 citations)—and the practical deployment of self-organizing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Local ant system for allocating robot swarms to time-constrained tasks26 citations · 2018
- 3Task Allocation Strategy for Time-Constrained Tasks in Robots Swarms17 citations · 2013
- 4
- 5Modeling Robot Swarms Using Integrals of Birth-Death Processes14 citations · 2016
- 6Collective Lévy Walk for Efficient Exploration in Unknown Environments13 citations · 2018
- 7
- 8
- 9Self-Organized Cooperation in Swarm Robotics12 citations · 2011
- 10