Track 11 Chair(s)


Mehdi Modarressi, University of Tehran, Iran






Andrea Acquaviva, Politecnico di Torino, Italy



Track 11 PC members

  • Adel Ahmadyan, SNAP, USA
  • Ali Shafiee, Samsung, USA
  • Mostafa Ersali Salehi Nasab, University of Tehran, Iran
  • Mehdi Kamal, University of Tehran, Iran

Topics of Interest

  • Conventional hardware (i.e. VLSI, FPGAs) and innovative hardware (i.e., memristor) implementation of Neuromorphic systems
  • Algorithm, and architecture co-optimization for efficient machine-learning hardware design
  • Models for neurons and synapses;
  • Spiking neuro-inspired architectures building blocks;
  • Reliable communication networks for neuro-inspired chips/systems;
  • Reconfigurability and adaptability methods;
  • Deep learning models;
  • New applications of on-chip learning (i.e., mobile devices, IoT).