Alejandro Linares-Barranco

About

Alejandro Linares-Barranco is a pioneering researcher at the intersection of neuromorphic engineering, robotics, and bio-inspired computing. His work centers on translating principles from biological neural systems into practical hardware implementations, with a particular focus on spike-based processing, FPGA architectures, and sensorimotor control for robotics. Linares-Barranco's most celebrated contributions involve developing neuro-inspired spike-based controllers for robotic systems, including a landmark PID motor controller implemented in VHDL for FPGAs (76 citations) and the NeuroPod spiking central pattern generator applied to legged robotics (66 citations). His research has advanced the integration of Dynamic Vision Sensors — silicon retinas that mimic the human eye's event-driven output — into real-time robotic pipelines, demonstrating complete spike-based architectures from sensing to motor control. His work on low-latency FPGA-based event filtering (48 citations) has been particularly influential for the neuromorphic vision community. Beyond motor control, he has explored neuromorphic sensory fusion, combining auditory and visual processing for autonomous navigation, and has contributed to fault-tolerant, self-adaptive spiking systems. More recently, his interests have extended to in-memory computing and meta-learning with phase-change memory. With publications spanning nearly two decades and hundreds of citations, Linares-Barranco stands as a significant figure in embodied neuromorphic intelligence.

Research Focus

Key Achievements

Top Papers

1. 1
   A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

   76 citations · 2012
2. 2
   Neuropod: A real-time neuromorphic spiking CPG applied to robotics

   66 citations · 2019
3. 3
   Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

   54 citations · 2013
4. 4
   Low Latency Event-Based Filtering and Feature Extraction for Dynamic Vision Sensors in Real-Time FPGA Applications

   48 citations · 2019
5. 5
   Using FPGA for visuo-motor control with a silicon retina and a humanoid robot

   33 citations · 2007
6. 6
   Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance

   31 citations · 2019
7. 7
   ED-BioRob: A Neuromorphic Robotic Arm With FPGA-Based Infrastructure for Bio-Inspired Spiking Motor Controllers

   27 citations · 2020
8. 8
   AER Neuro-Inspired interface to Anthropomorphic Robotic Hand

   27 citations · 2006
9. 9
   Rapid learning with phase-change memory-based in-memory computing through learning-to-learn

   22 citations · 2025
10. 10
    Case study: Bio-inspired self-adaptive strategy for spike-based PID controller

    19 citations · 2015

Key Collaborators

Contact & Links