Sanaz Mostaghim

About

Sanaz Mostaghim is a prominent researcher whose work spans evolutionary robotics, swarm intelligence, multi-agent systems, and computational intelligence. Based at the intersection of biological inspiration and autonomous systems, her research tackles some of the most challenging problems in coordinating intelligent agents at scale. Mostaghim's early landmark contribution introduced decentralized evolutionary frameworks for robotic control using finite state machines, earning 43 citations and establishing a foundation for online adaptive robotics. Her sustained focus on swarm robotics has yielded influential advances in collective decision-making, particularly through distributed Bayesian hypothesis testing and belief sharing—work that addresses how robot swarms can reach consensus without centralized control. These studies have collectively garnered nearly 40 citations, reflecting their significance to the swarm intelligence community. Her research further extends to energy-aware navigation for aerial micro-robots, where she developed PSO-based strategies that account for battery constraints and environmental dynamics—a practical contribution to real-world drone deployment. Her work on scalable multi-agent pathfinding and ant colony optimization-based task allocation demonstrates remarkable breadth across optimization and robotics planning. Complementing her research, her textbook *Introduction to Computational Intelligence* underscores her commitment to education in this field. Altogether, Mostaghim's body of work represents a cohesive and impactful career at the frontier of autonomous intelligent systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Decentralized evolution of robotic behavior using finite state machines

   43 citations · 2009
2. 2
   On the Scalable Multi-Objective Multi-Agent Pathfinding Problem

   27 citations · 2020
3. 3
   Collective Decision Making in Swarm Robotics with Distributed Bayesian Hypothesis Testing

   19 citations · 2020
4. 4
   Discrete collective estimation in swarm robotics with distributed Bayesian belief sharing

   18 citations · 2021
5. 5
   Energy Aware Particle Swarm Optimization as search mechanism for aerial micro-robots

   15 citations · 2016
6. 6
   Introduction to Computational Intelligence

   14 citations · 2016
7. 7
   Discrete Collective Estimation in Swarm Robotics with Ranked Voting Systems

   12 citations · 2021
8. 8
   Ant Colony Optimization based Multi-Robot Planner for Combined Task Allocation and Path Finding

   11 citations · 2020
9. 9
   Energy-saving decision making for aerial swarms: PSO-based navigation in vector fields

   11 citations · 2017
10. 10
    Generic Component-Based Mission-Centric Energy Model for Micro-Scale Unmanned Aerial Vehicles

    10 citations · 2020

Key Collaborators

Contact & Links