The University of Massachusetts Amherst
 
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Qiangfei Xia

Assistant Professor
  • Energy-efficient hardware systems for machine intelligence, security, sensing and communication
  • Emerging nanoelectronic devices: design, characterization and understanding
  • Enabling fabrication and three-dimensional heterogeneous integration technologies

Current Research
Our lab is developing compact, fast and power efficient personal health monitors. The technology can potentially solve problems in data storage, diagnosis time and power consumption for these sensors. Another example is a one-drop device that could provide on-the-spot cancer detection, glucose testing, or iron counts, etc.

As data is continuously collected from personal health monitors, high density, large capacity, and fast data storage with low power consumption become a critical component. We are working on a novel non-volatile memory technology called the “resistance switch” or “memristor”, which allows for universal data storage that is more densely packed and information be stored to the device without a constant power source.

We are also developing nanofluidic channels that enable the transport and analysis of tiny biological molecules. These nanoscale channels will be integrated with terahertz circuits for on-the-spot diagnosis of cancer and other diseases, leading to faster and improved treatments.

With the two technologies combined, patients may soon be able to take potentially life-saving measurements continuously throughout the day.

Learn more at nano.ecs.umass.edu

Academic Background

  • BE Shanghai Jiao Tong University, 1998
  • MS Shanghai Jiao Tong University, 2001
  • PhD Princeton University, 2007
Memristive crossbar arrays for brain-inspired computing Qiangfei Xia and J.J. Yang Nature Materials 18, 309-323(2019). (Invited Review) DOI: 10.1038/s41563-019-0291-x
Reinforcement learning with analogue memristor arrays Z. Wang, C. Li, W. Song, M. Rao, D. Belkin, Y. Li, P. Yan, H. Jiang, P. Lin, M. Hu, J.P. Strachan, N. Ge, M. Barnell, Q. Wu, A.G. Barth, Q. Qiu, R.S. Williams, Qiangfei Xia and J.J. Yang Nature Electronics 2, 115-124(2019). DOI: 10.1038/s41928-019-0221-6
Long short-term memory networks in memristor crossbar arrays C. Li, Z. Wang, M. Rao, D. Belkin, W. Song, H. Jiang, P. Yan, Y. Li, P. Lin, M. Hu, N. Ge, J.P. Strachan, M. Barnell, Q. Wu, R.S. Williams, J.J. Yang and Qiangfei Xia Nature Machine Intelligence 1, 49-57(2019). DOI: 10.1038/s42256-018-0001-4
Memristor crossbar arrays with 6-nm half-pitch and 2-nm critical dimension S. Pi, C. Li, H. Jiang, W. Xia, H.L. Xin, J.J. Yang and Qiangfei Xia Nature Nanotechnology 14, 35-39(2019). DOI: 10.1038/s41565-018-0302-0
A provable key destruction scheme based on memristive crossbar arrays H. Jiang, C. Li, R. Zhang, P. Yan, P. Lin, Y. Li, J.J. Yang, D. Holcomb and Qiangfei Xia Nature Electronics 1, 548-554(2018). DOI: 10.1038/s41928-018-0146-5
Capacitive neural network with neuro-transistors Z. Wang, M. Rao, J.-W. Han, J. Zhang, P. Lin, Y. Li, C. Li, W. Song, S. Asapu, R. Midya, E. Zhuo, H. Jiang, J.H. Yoon, N.K. Upadhyay, S. Joshi, M. Hu, J.P. Strachan, M. Barnell, Q. Wu, H. Wu, Q. Qiu, R.S. Williams, Qiangfei Xia and J.J. Yang Nature Communications 9, 3208(2018). DOI: 10.1038/s41467-018-05677-5
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks C. Li, D. Belkin, Y. Li, P. Yan, M. Hu, N. Ge, H. Jiang, E. Montgomery, P. Lin, Z. Wang, W. Song, J.P. Strachan, M. Barnell, Q. Wu, R.S. Williams, J.J. Yang, and Qiangfei Xia Nature Communications 9, 2385(2018). DOI: 10.1038/s41467-018-04484-2
Fully memristive neural networks for pattern classification with unsupervised learning Z. Wang, S. Joshi, S. Savel'ev, W. Song, R. Midya, Y. Li, M. Rao, P. Yan, S. Asapu, Y. Zhuo, H. Jiang, P. Lin, C. Li, J.H. Yoon, N.K. Upadhyay, J. Zhang, M. Hu, J.P. Strachan, M. Barnell, Q. Wu, H. Wu, R.S. Williams, Qiangfei Xia, and J.J. Yang Nature Electronics 1, 137-145(2018). DOI: 10.1038/s41928-018-0023-2
An artificial nociceptor based on a diffusive memristor J.H. Yoon, Z. Wang, K.M. Kim, H. Wu, V. Ravichandran, Qiangfei Xia, C.S. Hwang and J.J. Yang Nature Communications 9, 417(2018). DOI: 10.1038/s41467-017-02572-3
Analogue signal and image processing with large memristor crossbars C. Li, M. Hu, Y. Li, H. Jiang, N. Ge, E. Montgomery, J. Zhang, W. Song, N. Davila, C.E. Graves, Z. Li, J. P. Strachan, P. Lin, Z. Wang, M. Barnell, Q. Wu, R.S. Williams, J.J. Yang, and Qiangfei Xia Nature Electronics 1, 52-59(2018). DOI: 10.1038/s41928-017-0002-z (Cover article of the inaugural issue)

Emerging nanoelectronic devices, Nanofluidic channels, Hybrid nano/CMOS systems for biomedical applications, Enabling nanofabrication and integration technologies. Learn more at nano.ecs.umass.edu

 
Contact Info

Electrical and Computer Engineering
201D Marcus Hall
100 Natural Resources Road
Amherst, MA 01003

(413) 545-4571
qxia@ecs.umass.edu

nano.ecs.umass.edu/