Embedded Files
About me
About me
My name is Wei Wang (王伟 in Chinese). I am now a senior Scientist at Peng Cheng Laboratory (鹏城实验室), Shenzhen, China.
My research interests include neuromorphic computing, resistive switching devices (memristor, RRAM, ReRAM, CBRAM), Semiconductor physics, nano electronic devices, etc.
Email: wangweifcc (at) gmail.com, wangwei (at) pcl.ac.cn
You can also find my academic tracks on other sites:
Google Scholar: https://scholar.google.it/citations?user=b_HUmnWHeiMC&hl=en
Research Gate: https://www.researchgate.net/profile/Wei_Wang1054
Web of Science: https://www.webofscience.com/wos/author/record/1069888
Projects
Projects
Y-Flash memristor and memristive deep belief networks
Y-Flash memristor and memristive deep belief networks
Switching mechinsm and compact modeling of Y-Flash memristors
Memristive deep belief networks (DBNs)
Y-Flash based memristive DBN
Simulation and modeling of volatile memristive devices
Simulation and modeling of volatile memristive devices
Molecular dynamic simulation of the nanoscale filament shape evolution
Compact modelling of the device characteristics
Physical understanding of the surface ionic transport
Spiking neural network with non-volatile synapses
Spiking neural network with non-volatile synapses
Nonvolatile RRAM devices as artificial synapses
Learning and recognizing spatiotemporal spiking patterns
Volatile synapses enabled physically spatiotemporal processing
Volatile synapses enabled physically spatiotemporal processing
Volatie RRAM as short memory devices
Artificial retina based on short memory devices for motion detection
News
News
06/2025
Our work titled "Multiphysics-Coupled Ionic Migrations in Understanding Resistive Switching of Oxygen Vacancy-Based Resistive Random Access Memory (RRAM)" has been published in IEEE Transactions on Electron Devices.
A multiphysics TCAD simulator model is proposed for Oxide RRAM device. The role of thermal distribution in filament formation and retention is analyzed.
Thanks for the hardwork by Dr. Yang Li and other collaborators.
05/2025
Our work titled "Single pulse blind-write with gradient accumulation strategy tolerant to non-idealities of memristive synapse for in-memory learning" has been Journal of Physics D: Applied Physics.
Thanks for the hardwork by Mr. Linkun Wang and other collaborators.
11/2024
I gave a talk in MEMRISYS 2024 Seoul, Korea 10-13 Nov 2024.
The title is "Highly efficient neuromorphic deep learning enabled by binary-stochasticity", mainly focused on our work published in Advanced Intelligent System, 2023.
Check the slides here.
20241111_Pres_Memrisys_Wei.pdf
10/2024
Our work titled "Compact Modeling of the Pulse Modulation of the Resistive Switching Memory for Closed-Loop Multibit Write Operation" has been published in IEEE Transactions on Electron Devices.
A compact and accurate compact model for the pulse write behavior of RRAM is proposed and used to predict the number of pulses for read-write-verify scheme for arbitrary multi-level bits.
Thanks for the hardwork by Mr. Wenfeng Jiang and other collaborators.
06/2024
Together with Dr. Yang Li and Dr. Ming Wang, we analysis the difficulties and challenges to realize in-memory learning using emerging resistive artificial synaptic array. We published a review paper in Neuromorphic Computing and Engineering in this topic.
12/2023
Our work titled "Binary-Stochasticity-Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better-than-Software Accuracy" has been published in Advanced Intelligent System.
A new learning algorithm for in-memory learning in RRAM based neuromorphic network is proposed. All signals, including forward signals, backward errors, derivatives of activation fuction are highly quantized, i.e. binarized, with the help of device noise. The hardware implementation of a neural network is highly efficient and can have better performance than the floating-point conterpart in software. Thanks for the hardwork by Dr. Yang Li and other collaborators.
https://advanced.onlinelibrary.wiley.com/doi/10.1002/aisy.202300399
12/2022
Our paper titled "A memristive deep belief neural network based on silicon synapses" has been published in Nature Electronics. Thanks for the hard work from all of the coauthors and supports from the colleagues in Techion Asic2 Lab!
02/2022
Our paper with the title of "Efficient Training of the Memristive Deep Belief Net Immune to Non-Idealities of the Synaptic Devices" has been published in Advanced Intelligent System. Thanks for the hard work from all of the coauthors and supports from the colleagues in Techion Asic2 Lab!
https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202100249
01/2022
I have moved back to China, and started a new position at Peng Cheng Laboratory in Shenzhen!
12/2021
Our paper about the operation mechanims and compact modeling of Y-Flash memristors has been published in Applied Physics Letters. The work is a collabrated results of Technion and TowerJazz Semiconductor. Thanks for the hard work from all of the coauthors and supports from the colleagues in Techion Asic2 Lab.
07/2021
A review paper with the title of "Memristive Crossbar Arrays for Storage and Computing Applications" was published in Advanced Intelligent Systems.
https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202100017
06/2021
Dr. Ming Wang, Dr. Erika Covi, Dr. Gianluca Milano and me are co-editing a special issue "Devices, Architectures, and Applications of Neuromorphic Computing" on Electronics. Welcome for submssions of your extraordinary works! https://www.mdpi.com/journal/electronics/special_issues/NC_electronics
04/2021
Our paper with the titile of "Neuromorphic Motion Detection and Orientation Selectivity by Volatile Resistive Switching Memories" is now published in Advanced Intellegent Systems.
In this paper we take inspiration from the biological DS ganglion cells in the retina, and demonstrate the motion detection in an artificial neural network made of volatile resistive switching devices with short-term memory effects. The motion detection arises from the spatiotemporal correlation between the adjacent excitatory and inhibitory receptive fields with short-term memory synapses, closely resembling the physiological response of DS ganglion cells in the retina. The work supports real-time neuromorphic processing of sensor data by exploiting the unique physics of innovative memory devices.
The paper is selected to the collection of Editor's Choice of Advanced Intellegent Systems.
12/2020
Our review paper about "Integration and Co-design of Memristive Devices and Algorithms for Artificial Intelligence" is published in iScience by the Cell press. The paper summarized the challenges and opportunities of using memristive devices in deep learning accelerators and brain-like computing.
The paper is collaborately wrote with the help of Prof. Joshua Yang from University of Southern California, Prof. Daniele Ielmini from Politecnico di Milano, and other top scientists in the field.
09/2020
I am awarded by the Andrew and Erna Finci Viterbi Fellowship for 2020-2021 academic year.
Andrew and Erna Finci Viterbi have a long history of supporting the Technion and Israel. The faculty of Electrical Engineering in Technion are now named after them. Andrew Viterbi is one of the cofounder of Qualcomm Inc. and invented the Viterbi algorithm, an important algorithm for wireless communication.
Here is more information about the Viterbis and their support to Technion, especially the support to the faculty of Electrical Engineering.
12/2019
Participanted in IEDM 2019 in San Fransicico on Dec. 9th-11th.
Our paper titled "Modeling of switching speed and retention time in volatile resistive switching memory by ionic drift and diffusion" was presented in Session 32: Modeling and Simulation.
01/2019
My first-authored paper was published in Nature Communications on Jan. 8th, 2019.
Learn more behind the paper from the blog (https://go.nature.com/2FkYnKe) ‘Atomic surfing controls the memory lifetime’ on Nature Device & Materials Engineering Community website, by our corresponding author, Prof. Daniele Ielmini.
12/2018
My first-authored work titled "Physics-based modeling of volatile resistive switching memory (RRAM) for crosspoint selector and neuromorphic computing", was presented in 2018 IEDM conferences which was hold in Dec. 3rd-5th, 2018, San Francisco. The paper was also featured in the promotion video of the IEDM. View the video on YouTube .
Google Sites
Report abuse