Chua Memristor CenterProf. Joshua Yang
Department of Electrical and Computer Engineering
University of Southern California
3740 McClintock Avenue, EEB 340
Los Angeles, CA 90089-2562, USA
Email: joshua.yang@usc.edu
Professor J. Joshua Yang is the Arthur B. Freeman Chair Professor in the Department of Electrical and Computer Engineering at the University of Southern California (USC). A pioneer in neuromorphic computing and emerging memory technologies, he is best known for his groundbreaking work on resistive switching devices and memristive systems.
He earned his Ph.D. from the University of Wisconsin–Madison, following a Bachelor’s from Southeast University. Prior to joining USC, he was a lead researcher at HP Labs and later a professor at the University of Massachusetts Amherst. His work has resulted in over 120 granted patents and numerous high-impact publications in top journals such as Nature, Science, and IEEE.
Professor Yang currently directs the Center of Excellence on Neuromorphic Computing, co-directs USC’s Institute for the Future of Computing, and is the Scientific Advisory Board Chairman of TetraMem Inc., a startup developing AI hardware.
“Memristive devices for computing”
Authors: J. Joshua Yang, Dmitri B. Strukov, Duncan R. Stewart
https://doi.org/10.1038/nnano.2012.240
“Memristive switching mechanism for metal/oxide/metal nanodevices”
Authors: J. Joshua Yang, Michael D. Pickett, Xiaoqing Li, D.A.A. Ohlberg, Duncan R. Stewart, R. Stanley Williams
https://doi.org/10.1038/nnano.2008.160
“Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing”
Authors: Z. Wang, S. Joshi, S.E. Savel’ev, H. Jiang, R. Midya, P. Lin, M. Hu, N. Ge, J.P. Strachan, Z. Li, Q. Wu, M. Barnell, G.-L. Li, H. Xin, R.S. Williams, J.J. Yang, Q. Xia
https://doi.org/10.1038/nmat4756
“‘Memristive’ switches enable ‘stateful’ logic operations via material implication”
Authors: J. Borghetti, G.S. Snider, P.J. Kuekes, J. Joshua Yang, D.R. Stewart, R.S. Williams
https://doi.org/10.1038/nature08940
“Analogue signal and image processing with large memristor crossbars”
Authors: C. Li, M. Hu, Y. Li, H. Jiang, N. Ge, E. Montgomery, J. Zhang, W. Song, P. Lin, Z. Wang, N. Davila, C.E. Graves, Z. Li, J.P. Strachan, M. Barnell, Q. Wu, R.S. Williams, J.J. Yang, Q. Xia
https://doi.org/10.1038/s41928-017-0002-z
“Efficient and self-adaptive in-situ learning in multilayer memristor neural networks”
Authors: C. Li, D. Belkin, Y. Li, P. Yan, M. Hu, N. Ge, H. Jiang, E. Montgomery, P. Lin, Z. Wang, W. Song, N. Davila, C.E. Graves, Z. Li, J.P. Strachan, M. Barnell, Q. Wu, R.S. Williams, J.J. Yang, Q. Xia
https://doi.org/10.1038/s41467-018-04484-2
“Fully memristive neural networks for pattern classification with unsupervised learning”
Authors: Z. Wang, S. Joshi, S. Savel’ev, W. Song, R. Midya, Y. Li, M. Rao, P. Yan, J.P. Strachan, M. Barnell, Q. Wu, M. Hu, H. Jiang, N. Ge, R.S. Williams, Q. Xia, J.J. Yang
https://doi.org/10.1038/s41928-018-0059-6
“Resistive switching materials for information processing”
Authors: Z. Wang, H. Wu, G.W. Burr, C.S. Hwang, K.L. Wang, Q. Xia, J.J. Yang
https://doi.org/10.1038/s41578-019-0148-z
“Memristor-based analog computation and neural network classification with a dot product engine”
Authors: M. Hu, C.E. Graves, C. Li, Y. Li, N. Ge, E. Montgomery, N. Davila, H. Jiang, P. Lin, C. Wu, J. Zhang, Z. Wang, Z. Li, J.P. Strachan, M. Barnell, Q. Wu, R.S. Williams, J.J. Yang, Q. Xia
https://doi.org/10.1002/adma.201705914
“A fully hardware-based memristive multilayer neural network”
Authors: S. Pi, S. Lin, Q. Xia
https://doi.org/10.1126/sciadv.abj4801
