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ICT Open 2022

Neuromorphic Computing and Engineering

Neuromorphic computing and engineering have recently received considerable attention as paradigms for brain-inspired Artificial Intelligence (AI) applications. These disciplines deliver promising technological solutions for implementing efficient sensory, learning, and processing systems, as well as autonomous agents able to operate in real-world conditions.

The research on neuromorphic systems, originally based on CMOS technology, has gained momentum towards new horizons thanks to the emergence of novel devices and materials for brain-inspired computing (e.g. in-memory computing). These new developments face unusual challenges of creating new models of computations, tools, and architectures that can best exploit the sophistication and complexity of the inhomogeneous, low-power, dense, and parallel elements. 

The most important research actors in the Netherlands, both at the academic and industrial level, are becoming increasingly active on these topics. This track aims to provide an opportunity for Dutch researchers working in these fields to discuss, network, and broaden the impact of their research. 

Elisabetta Chicca - University of Groningen
Federico Corradi - Eindhoven University of Technology

Invited speakers

Herbert Jaeger

Thursday 7 April
11:30 - 12:00 hour

Guido de Croon

Thursday 7 April
14:30 - 15:00 hour

Oral presentation round 1

Training Dynamic Spiking Neural Network via Forward Propagation Through Time

Bojian Yin (CWI) (e.a.)

Thursday 7 April
12:00 - 12:15 hour

Modelling of networks of memristors

Bart Besselink (Rijksuniversiteit Groningen) (e.a.)

Thursday 7 April
12:15 - 12:30 hour

Oral presentation round 2

Efficient Synaptic Memory Utilization on Digital Neuromorphic Hardware

Sherif Eissa (TU Eindhoven) (e.a.)

Thursday 7 April
15:00 - 15:15 hour

A mixed-signal CMOS interpretation: Learning by the Dendritic Prediction of Somatic Spiking

Ole Richter (Rijksuniversiteit Groningen) (e.a.)

Thursday 7 April
15:15 - 15:30 hour


Neuromorphic extreme edge computing for touch sensors test

Michele Mastella (Rijksuniversiteit Groningen) (e.a.)

Distributed Finite State Machines in Hyperdimensional Hopfield Networks

Madison Cotteret (Rijksuniversiteit Groningen) (e.a.)

Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks

Jesse Hagenaars (TU Delft) (e.a.)

Self-organizing neural networks: How can we learn online, efficiently and without supervision?

Lyes Khacef (Rijksuniversiteit Groningen) (e.a.)

Robust Learning Rule for Memristor-based Synapses in Spiking Neural Networks

Thomas Tiotto (Rijksuniversiteit Groningen) (e.a.)

Calcium-based Hebbian-rule enables rate and time-dependent synaptic dynamics

Willian Soares GirĂ£o (Rijksuniversiteit Groningen) (e.a.)

Local Unsupervised Learning of Multimodal Event-Based Data with Spiking Neural Networks

Julian Lopez Gordillo (Rijksuniversiteit Groningen) (e.a.)

Integrate-and-fire neuron circuits using HfO2-based ferroelectric field effect transistors

Philipp Klein (Rijksuniversiteit Groningen) (e.a.)

SENeCA: Scalable Energy-efficient Neuromorphic Computer Architecture

Amirreza Yousefzadeh (Stichting IMEC Nederland) (e.a.)

Demo stands

Live Demonstration: Sound-Source-Localization with the Time Difference Encoder

Thorben Schoepe (Rijksuniversiteit Groningen) (e.a.)

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