Alejandro Ribeiro

About

Alejandro Ribeiro is a leading researcher at the intersection of multi-robot systems, wireless communications, and machine learning, whose work has fundamentally shaped how autonomous robot teams coordinate in complex, real-world environments. His research addresses one of robotics' most pressing challenges: enabling decentralized robot swarms to move intelligently while maintaining robust communication networks. Ribeiro's pioneering contributions span graph neural network-based control, where his 2020 paper on decentralized multi-robot path planning (263 citations) demonstrated that learned communication strategies can outperform hand-crafted heuristics. His earlier work establishing cyber-physical controllers for robot team connectivity (155 citations, 2011) laid essential theoretical groundwork for the field. Across his portfolio, Ribeiro has consistently tackled the deeply coupled "mobility and communication" problem, showing that movement and networking must be co-optimized rather than treated independently — a perspective reflected in multiple highly cited works from 2010 through 2017. More recently, he has championed graph neural networks as a unifying framework for swarm intelligence, with applications ranging from coverage and exploration (67 citations) to distributed controller learning (67 citations). His cumulative impact, exceeding 900 citations across just these ten papers, marks him as an indispensable voice in modern multi-agent robotics research.

Research Focus

Key Achievements

Top Papers

1. 1
   Graph Neural Networks for Decentralized Multi-Robot Path Planning

   263 citations · 2020
2. 2
   Robust Control for Mobility and Wireless Communication in Cyber–Physical Systems With Application to Robot Teams

   155 citations · 2011
3. 3
   Robust Control of Mobility and Communications in Autonomous Robot Teams

   116 citations · 2013
4. 4
   Network Integrity in Mobile Robotic Networks

   101 citations · 2012
5. 5
   Concurrent Control of Mobility and Communication in Multirobot Systems

   72 citations · 2017
6. 6
   Multi-Robot Coverage and Exploration using Spatial Graph Neural Networks

   67 citations · 2021
7. 7
   Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks

   67 citations · 2019
8. 8
   ROS-NetSim: A Framework for the Integration of Robotic and Network Simulators

   44 citations · 2021
9. 9
   Adaptive Communication-Constrained Deployment of Unmanned Vehicle Systems

   40 citations · 2012
10. 10
    Mobility & routing control in networks of robots

    30 citations · 2010

Key Collaborators

Contact & Links