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Zhengya Zhang

First programmable memristor computer aims to bring AI processing down from the cloud

Circuit elements that store information in their electrical resistances enable a brain-like form of computing, storing and processing information in the same place.

Prof. Zhengya Zhang receives CoE undergraduate education award

Prof. Zhang receives outstanding evaluations from students and opens their imagination to research in the field of VLSI circuits and systems.

2015 promotions of our faculty – congratulations!

Congratulations to the faculty members that received promotions this year.

Thomas Chen earns NSF Graduate Research Fellowship for research in artificial neural networks for computer vision

Thomas and his group are working to improve upon artificial neural network design through a process called sparse coding.

Chia-Hsiang Chen awarded Intel PhD Fellowship

Chia-Hsiang’s research focuses on designing low-power and error-resilient circuit techniques for digital signal processing applications.

Leaders in ultra low power cicuits and systems presenting at VLSI Circuits Symposium

All of the research being presented focuses on getting the absolute best performance from the tiniest circuits, sensors, and electronic devices.

Zhengya Zhang receives Intel Early Career Award

Zhang’s research is in the area of low-power and high-performance VLSI circuits and systems.

Researchers funded to develop a leap forward in Processor Architectures

The project proposes to produce a parallel heterogeneous 3D near-threshold computing system with unprecedented energy efficiency.

Zhengya Zhang receives NSF CAREER Award

The proposed research addresses the frontiers of error-correction coding and very-large-scale integration by advancing algorithms and circuit techniques.

Zhengya Zhang earns Best Paper Award at Symposium on VLSI Circuits

The resulting 65nm CMOS test chip achieved an energy efficiency of 21 pJ/bit making it a promising candidate for low-power, high-performance applications.