Guido Novati

ETH Zurich

Papers

2

Total Citations

459

H-Index

2

About

Guido Novati is a leading researcher at the intersection of fluid dynamics and artificial intelligence, whose work has fundamentally reshaped our understanding of how organisms—and robots—can harness complex flow fields. His most celebrated contribution, the 2018 paper "Efficient collective swimming by harnessing vortices through deep reinforcement learning" (454 citations), revolutionized the field by demonstrating that fish in schooling formations do not merely endure vortex wakes but actively exploit them for energy savings. Using deep reinforcement learning, Novati showed that swimmers can learn to extract mechanical energy from their neighbors' vortices, providing a powerful computational explanation for the evolutionary advantages of collective behavior. Building on this, his 2021 work on "Learning efficient navigation in vortical flow fields" (5 citations) extends these principles to robotics, tackling the challenge of point-to-point navigation in time-varying currents with limited sensory information. This work is pivotal for autonomous ocean surveying, where robots must adapt to unpredictable flows. Novati’s research is a landmark in bio-inspired robotics and active matter, offering both profound biological insights and practical tools for next-generation autonomous systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
459
Total Citations
230
Avg Citations/Paper
🏆 Most Cited Paper
Efficient collective swimming by harnessing vortices through deep reinforcement learning
454 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: ETH Zurich

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago