Neuromorphic physics harnesses multifunctional nanodevices to improve classical and quantum neural networks. Drawing inspiration from the brain, we leverage fundamental physics principles to enhance neuron- and synapse-mimicking components as well as learning algorithms. You can find our review article on this topic here: Nature Review Physics 2020 [arXiv]. Our research designs ultra-efficient devices that will analyze complex data and learn in real-time.
We are particularly focusing on:
algorithms
The group was created by Julie Grollier in 2015 and is now composed of four senior researchers from CNRS and Thales with Danijela Marković, Frank Mizrahi and Dédalo Sanz Hernandez,
(CNRS)
the PhD students,
Quantum neural networks
Dongshu Liu
Algorithms
Quantum neuro computing
Spintronics
Post-docs,
Code development
Algorithms
Master students,
and you can meet here our former group members:
PhD in Politecnico di Torino
Professor at IIT Gandhinagar
Researcher at VTT Finland
Post-doc at Cornell Univ.
Post-doc at Aachen University
research engineer at Spin Ion
Research engineer Thales
CEA researcher SPINTEC
FNRS researcher (Université de Louvain la Neuve)
