Arindam Basu | City University of Hong Kong

Yoeri van de Burgt | Eindhoven University of Technology

Geoffrey W. Burr | IBM Research - Almaden

Saptarshi Das | Penn State University

Wulfram Gerstner | Ecole Polytechnique Federale de Lausanne (EPFL)

Paschalis Gkoupidenis | Max Planck Institute for Polymer Research

Julie Grollier | Unité Mixte de Physique CNRS/Thales

Donhee Ham | Harvard University.

Daniele Ielmini | Politecnico di Milano

Giacomo Indiveri | University of Zurich and ETH Zurich

Brett J. Kagan | Cortical Labs 

Hans Kleemann | Technical University of Dresden

Suhas Kumar | Sandia National Laboratories

Mario Lanza | King Abdullah University of Science and Technology

Wei D Lu | University of Michigan Ann Arbor

Nripan Mathews | Nanyang Technological University

David Moss | Swinburne University of Technology

Emre Neftci | Forschungszentrum Jülich

Shriram Ramanathan | Purdue University

Kaushik Roy | Purdue University

Yulia Sandamirskaya | Intel Labs

Francesca Santoro | RWTH Aachen University 

Sean E. Shaheen | University of Colorado Boulder

Dmitri Strukov | UC Santa Barbara

Venky Venkatesan | The University of Oklahoma

Stanley Williams | Texas A&M University

Huaqiang Wu | Tsinghua University

Joshua Yang | University of Southern California

Shimeng Yu | Georgia Institute of Technology

nanoGe aims to give equal opportunities to participants who work for an institution whose country is listed as "Developing country" (see here) by offering reduced fee tickets.

Get in touch with us before register at the conference and before the deadline, January 16th 2023*.

For any further information we are glad to support at office@scito.org

* Applications will only be accepted for participants who use the official email of their institution.

nanoGe offers group discounts. To register a group, contact us at office@scito.org

You are invited to the Online Conference on Neuromorphic Materials, Devices, Circuits and Systems (NeuMatDeCaS) that will take place from the 23rd to the 25th of January 2023.

The human brain performs complex cognitive tasks with a mere 20W of power, and hence serves as an inspiration for the next generation of low-power computer systems. The co-location of computation and memory in the brain motivates for non-Von Neumann systems, subverting the memory wall observed in conventional computers. Moreover, the structure of the brain as an interconnected network of neurons and synapses as well as its operation give rise to many algorithmic advancements including deep neural networks (DNNs) and further bio-inspired spiking neural networks (SNNs). Neuromorphic computing opens up many opportunities in material discovery, device engineering, circuit design and algorithm development to tailor systems that can learn from unstructured data. The goal of this conference is to provide a forum for discussing interdisciplinary research in brain-inspired computing, with an emphasis on emerging understanding of synaptic and neuronal processes in devices and systems. The scope of this conference will cover:

(1) Employing emerging memristive and memtransistive materials and novel device physics to create neuromorphic systems and in-memory computing applications,

(2) Exploration of the principles of learning such as Hebbian learning, synaptic competition, winner-take-all mechanism, associative learning, and

(3) Investigation of computational frameworks for supervised learning, unsupervised learning, reinforcement learning, reservoir computing, one-shot learning and beyond.