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Overview

Miao Hu is a researcher affiliated with Binghamton University in the United States. Their work spans multiple areas of computer science and engineering, with a particular focus on advancing memory technologies, neural computing, and security methods.

The main fields of study addressed by Miao Hu include Computer Science and Engineering. Within these, their research delves into subfields such as Electrical and Electronic Engineering, Computer Networks and Communications, Plant Science, Computer Vision and Pattern Recognition, and Information Systems.

Miao Hu's research topics cover diverse areas, notably:

  • Advanced Memory and Neural Computing
  • Ferroelectric and Negative Capacitance Devices
  • CCD and CMOS Imaging Sensors
  • Advanced Malware Detection Techniques
  • Network Security and Intrusion Detection
  • Smart Agriculture and AI
  • Neural dynamics and brain function

Their publication record includes several influential papers across high-impact journals and conferences. Recent notable works include:

  • "Thousands of conductance levels in memristors integrated on CMOS" (2023), published in Nature
  • "Programming memristor arrays with arbitrarily high precision for analog computing" (2024), published in Science
  • "A hierarchical deep reinforcement learning model with expert prior knowledge for intelligent penetration testing" (2023), published in Computers & Security
  • "INNES: An intelligent network penetration testing model based on deep reinforcement learning" (2023), published in Applied Intelligence
  • "Mitigate Parasitic Resistance in Resistive Crossbar-based Convolutional Neural Networks" (2020), published in ACM Journal on Emerging Technologies in Computing Systems

Miao Hu frequently collaborates with other researchers in their field. Frequent co-authors include:

  • Qiangfei Xia
  • J. Joshua Yang
  • Wenhao Song
  • Wenbo Yin
  • Ning Ge

The venues where Miao Hu publishes reflect a range of disciplines and interdisciplinary interests, including:

  • Nature
  • Science
  • Computers & Security
  • Applied Intelligence
  • Industrial Crops and Products

Best Publications

  • ISAAC: a convolutional neural network accelerator with in-situ analog arithmetic in crossbars

    Ali Shafiee;Anirban Nag;Naveen Muralimanohar;Rajeev Balasubramonian

  • Analogue signal and image processing with large memristor crossbars

    Can Li;Miao Hu;Miao Hu;Yunning Li;Hao Jiang

  • Fully memristive neural networks for pattern classification with unsupervised learning

    Zhongrui Wang;Saumil Joshi;Sergey Savel’ev;Wenhao Song

  • Efficient and self-adaptive in-situ learning in multilayer memristor neural networks

    Can Li;Daniel Belkin;Daniel Belkin;Yunning Li;Peng Yan;Peng Yan

  • Memristor-Based Analog Computation and Neural Network Classification with a Dot Product Engine.

    Miao Hu;Catherine E. Graves;Can Li;Yunning Li

  • Dot-product engine for neuromorphic computing: programming 1T1M crossbar to accelerate matrix-vector multiplication

    Miao Hu;John Paul Strachan;Zhiyong Li;Emmanuelle M. Grafals

  • Memristor Crossbar-Based Neuromorphic Computing System: A Case Study

    Miao Hu;Hai Li;Yiran Chen;Qing Wu

  • Long short-term memory networks in memristor crossbars

    Can Li;Zhongrui Wang;Mingyi Rao;Daniel Belkin

  • Reinforcement learning with analogue memristor arrays

    Zhongrui Wang;Can Li;Wenhao Song;Mingyi Rao

  • Long short-term memory networks in memristor crossbar arrays

    Can Li;Can Li;Zhongrui Wang;Mingyi Rao;Daniel Belkin

  • In situ training of feed-forward and recurrent convolutional memristor networks

    Zhongrui Wang;Can Li;Can Li;Peng Lin;Mingyi Rao

  • Capacitive neural network with neuro-transistors.

    Zhongrui Wang;Mingyi Rao;Jin Woo Han;Jiaming Zhang

  • Rescuing Memristor-based Neuromorphic Design with High Defects

    Chenchen Liu;Miao Hu;John Paul Strachan;Hai (Helen) Li

  • Hardware realization of BSB recall function using memristor crossbar arrays

    Miao Hu;Hai Li;Qing Wu;Garrett S. Rose

  • Memristor-based approximated computation

    Boxun Li;Yi Shan;Miao Hu;Yu Wang

  • A Compact Memristor-Based Dynamic Synapse for Spiking Neural Networks

    Miao Hu;Yiran Chen;J. Joshua Yang;Yu Wang

  • Digital-assisted noise-eliminating training for memristor crossbar-based analog neuromorphic computing engine

    Beiye Liu;Miao Hu;Hai Li;Zhi-Hong Mao

  • Memristor crossbar based hardware realization of BSB recall function

    Miao Hu;Hai Li;Qing Wu;Garrett S. Rose

  • BSB training scheme implementation on memristor-based circuit

    Miao Hu;Hai Li;Yiran Chen;Qing Wu

  • Learning Driven Computation Offloading for Asymmetrically Informed Edge Computing

    Miao Hu;Lei Zhuang;Di Wu;Yipeng Zhou

Frequent Co-Authors

John Paul Strachan
John Paul Strachan Hewlett-Packard (United States)
J. Joshua Yang
J. Joshua Yang University of Southern California
Hai Li
Hai Li Duke University
Ning Ge
Ning Ge Tsinghua University
Qing Wu
Qing Wu United States Air Force Research Laboratory
R. Stanley Williams
R. Stanley Williams Texas A&M University
Qiangfei Xia
Qiangfei Xia University of Massachusetts Amherst
Zhiyong Li
Zhiyong Li Chinese Academy of Sciences
Garrett S. Rose
Garrett S. Rose University of Tennessee at Knoxville
Qinru Qiu
Qinru Qiu Syracuse University

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