The Online Conference on Neuromorphic Materials, Devices, Circuits and Systems (NeuMatDeCaS) took 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.
In this sense, the scope of this conference covered:
(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.
Rohit Abraham John
Department of Chemistry and Applied Bioscience
ETH Zürich, CH
Irem Boybat
IBM Research Europe
Zurich, CH
Jason Eshraghian
University of California, Santa Cruz
Simone Fabiano
Department of Science and Technology,
Linköping University, SE
- Materials & Devices: ReRAM, PCM, Ferroelectric, Spintronics, Organic, OECTs, Halide Perovskites, 2D transition metal dichalcogenides, Photonics.Tutorial session: Computational Neuroscience
- Circuits, Systems & Algorithms: In-sensory computing, In-memory computing, Deep neural networks (DNNs), Spiking neural networks (SNNs).
🏅 Best Contributed Talk prize valued at 200 € from APL Machine Learning: Piergiulio Mannocci from Politecnico di Milano, for his speech about Analogue in-memory computing for accelerating massive MIMO processing in 6G.
🏅 Prize for best run up oral contribution of a books coupon valued at $175 from Advanced Intelligent Systems: Yigit Demirag from University of Zurich and ETH Zurich, for his speech "Overcoming phase-change material non-idealities by meta-learning for adaptation on the edge".
🏅 Best Poster prize of a books coupon valued at $175 from Advanced Intelligent Systems: Daniela Rana from FZJ, Germany for her poster "Neuromorphic control of organic electrochemical transistors for the actuation of a robotic hand".
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*.
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* Applications will only be accepted for participants who use the official email of their institution.
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