Federico Pigozzi

About

Federico Pigozzi is a computational researcher whose work sits at the fascinating intersection of evolutionary computation, soft robotics, and artificial life. His research focuses primarily on voxel-based soft robots (VSRs) — modular, deformable artificial agents that serve as powerful platforms for exploring fundamental questions about embodied intelligence, biodiversity, and adaptive behavior. Pigozzi's most influential contribution, "Biodiversity in Evolved Voxel-Based Soft Robots" (2021, 49 citations), addresses how evolutionary algorithms can produce diverse yet equally capable robot morphologies, drawing inspiration from the resilience of biological ecosystems. This theme of bio-inspired diversity runs throughout his portfolio, with follow-up work examining the factors that shape both effectiveness and variety in evolved modular systems. A particularly distinctive strand of his research involves Hebbian learning — biologically plausible synaptic plasticity rules — applied to robot controllers, enabling agents to adapt during their lifetimes rather than relying solely on evolutionary optimization. His work on self-attention-based modular controllers further demonstrates his commitment to eliminating unrealistic engineering assumptions, such as explicit inter-module communication. With over 140 cumulative citations across a compact but impactful body of work, Pigozzi has established himself as a thoughtful voice in evolutionary robotics, contributing both technical innovations and broader reflections on the field's trajectory.

Research Focus

Key Achievements

Top Papers

1. 1
   Biodiversity in evolved voxel-based soft robots

   49 citations · 2021
2. 2
   Evolving modular soft robots without explicit inter-module communication using local self-attention

   26 citations · 2022
3. 3
   Factors Impacting Diversity and Effectiveness of Evolved Modular Robots

   18 citations · 2023
4. 4
   Evolving Hebbian Learning Rules in Voxel-Based Soft Robots

   14 citations · 2022
5. 5
   On the impact of body material properties on neuroevolution for embodied agents

   10 citations · 2022
6. 6
   Evolving Hebbian Learning Rules in Voxel-based Soft Robots

   7 citations · 2021
7. 7
   Evolving Modularity in Soft Robots Through an Embodied and Self-Organizing Neural Controller

   7 citations · 2022
8. 8
   Robots: the Century Past and the Century Ahead

   6 citations · 2022
9. 9
   Evolving Hebbian Learning Rules in Voxel-based Soft Robots

   4 citations · 2021
10. 10
    Shape Change and Control of Pressure-based Soft Agents

    3 citations · 2022

Key Collaborators

Contact & Links