Papers
6
Total Citations
142
H-Index
6
About
Nikolai F. Rulkov is a computational neuroscientist and robotics researcher whose work sits at the fascinating intersection of neurodynamics, biomimetic robotics, and real-time neural simulation. He is perhaps best known for his pioneering development of map-based neuronal models — discrete-time mathematical frameworks that efficiently capture the complex spiking and bursting dynamics of biological neurons. His 2016 work on quantization of these models for embedded systems (33 citations) demonstrated their remarkable utility in real-time neurobiological simulations, opening new pathways for hardware-constrained applications. Rulkov has made substantial contributions to biomimetic underwater robotics, particularly through his development of electronic nervous systems (ENS) to control lamprey-inspired robots. His landmark 2011 paper on lamprey-based robot control (42 citations) showcased how biologically realistic neural controllers could drive undulatory locomotion using shape memory alloy actuators — a striking proof-of-concept for neurorobotics. Complementary studies published in 2010 and 2011 further established feasibility frameworks for adaptive underwater robot control. His 2013 investigation into antiphase bursting in coupled neural populations illuminated fundamental mechanisms underlying central pattern generators in animal locomotion. Collectively, Rulkov's research has meaningfully advanced our understanding of how biological neural principles can be translated into functional engineered systems.
Research Focus
Key Achievements
Top Papers
- 1Controlling a lamprey-based robot with an electronic nervous system42 citations · 2011
- 2
- 3Controlling Biomimetic Underwater Robots With Electronic Nervous Systems25 citations · 2011
- 4Controlling Underwater Robots with Electronic Nervous Systems24 citations · 2010
- 5
- 6Controlling Underwater Robots with Electronic Nervous Systems9 citations · 2010