World's Best Scientists 2026 revealed!
Huazhong Yang

Huazhong Yang

D-Index & Metrics

Computer Science

D-Index
59
Citations
15706
World Ranking
3397
National Ranking
455

Electronics and Electrical Engineering

D-Index
57
Citations
15234
World Ranking
1941
National Ranking
335

Overview

Huazhong Yang is affiliated with Tsinghua University in China and has a significant body of research in engineering and computer science. Their work spans several subfields, primarily focusing on electrical and electronic engineering, computer vision and pattern recognition, artificial intelligence, aerospace engineering, and hardware and architecture.

The scientist's research topics include:

  • Advanced Memory and Neural Computing
  • Ferroelectric and Negative Capacitance Devices
  • Advanced Neural Network Applications
  • Semiconductor materials and devices
  • CCD and CMOS Imaging Sensors
  • Robotic Path Planning Algorithms
  • Advanced Vision and Imaging

Huazhong Yang has published extensively in several venues. The most frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Journal of Solid-State Circuits
  • IEEE Transactions on Circuits and Systems I Regular Papers
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • IEEE Transactions on Circuits & Systems II Express Briefs

Their recent papers demonstrate the breadth of their research interests. Notable publications include:

  • "Machine Learning for Electronic Design Automation: A Survey" (2021), published in ACM Transactions on Design Automation of Electronic Systems
  • "Inter-patient ECG arrhythmia heartbeat classification based on unsupervised domain adaptation" (2021), published in Neurocomputing
  • "Senputing: An Ultra-Low-Power Always-On Vision Perception Chip Featuring the Deep Fusion of Sensing and Computing" (2021), published in IEEE Transactions on Circuits and Systems I Regular Papers
  • "STICKER-IM: A 65 nm Computing-in-Memory NN Processor Using Block-Wise Sparsity Optimization and Inter/Intra-Macro Data Reuse" (2022), published in IEEE Journal of Solid-State Circuits
  • "MSP-MFCC: Energy-Efficient MFCC Feature Extraction Method With Mixed-Signal Processing Architecture for Wearable Speech Recognition Applications" (2020), published in IEEE Access

Frequent co-authors of Huazhong Yang include Yongpan Liu, Xueqing Li, Xuefei Ning, Yu Wang, and Jinshan Yue, with collaboration counts of 61, 46, 36, 32, and 19 papers respectively. This indicates active cooperation within a network of researchers in related fields.

Best Publications

  • Going Deeper with Embedded FPGA Platform for Convolutional Neural Network

    Jiantao Qiu;Jie Wang;Song Yao;Kaiyuan Guo

  • Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA

    Kaiyuan Guo;Lingzhi Sui;Jiantao Qiu;Jincheng Yu

  • IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—II: EXPRESS BRIEFS

    Yong Lian;Mohamad Sawan;Chacko John Deepu

  • Accurate temperature-dependent integrated circuit leakage power estimation is easy

    Yongpan Liu;Robert P. Dick;Li Shang;Huazhong Yang

  • Machine Learning for Electronic Design Automation: A Survey

    Guyue Huang;Jingbo Hu;Yifan He;Jialong Liu

  • [DL] A Survey of FPGA-based Neural Network Inference Accelerators

    Kaiyuan Guo;Shulin Zeng;Jincheng Yu;Yu Wang

  • FPMR: MapReduce framework on FPGA

    Yi Shan;Bo Wang;Jing Yan;Yu Wang

  • Technological Exploration of RRAM Crossbar Array for Matrix-Vector Multiplication

    Lixue Xia;Peng Gu;Boxun Li;Tianqi Tang

  • A 3us wake-up time nonvolatile processor based on ferroelectric flip-flops

    Unknown

  • Binary convolutional neural network on RRAM

    Tianqi Tang;Lixue Xia;Boxun Li;Yu Wang

  • MNSIM: Simulation Platform for Memristor-Based Neuromorphic Computing System

    Lixue Xia;Boxun Li;Tianqi Tang;Peng Gu

  • Technological exploration of RRAM crossbar array for matrix-vector multiplication

    Peng Gu;Boxun Li;Tianqi Tang;Shimeng Yu

  • Thermal vs Energy Optimization for DVFS-Enabled Processors in Embedded Systems

    Yongpan Liu;Huazhong Yang;R.P. Dick;H. Wang

  • A Survey of FPGA Based Neural Network Accelerator

    Kaiyuan Guo;Shulin Zeng;Jincheng Yu;Yu Wang

  • GraphH: A Processing-in-Memory Architecture for Large-Scale Graph Processing

    Guohao Dai;Tianhao Huang;Yuze Chi;Jishen Zhao

  • ForeGraph: Exploring Large-scale Graph Processing on Multi-FPGA Architecture

    Guohao Dai;Tianhao Huang;Yuze Chi;Ningyi Xu

  • Stuck-at Fault Tolerance in RRAM Computing Systems

    Lixue Xia;Wenqin Huangfu;Tianqi Tang;Xiling Yin

  • Ambient energy harvesting nonvolatile processors: from circuit to system

    Yongpan Liu;Zewei Li;Hehe Li;Yiqun Wang

  • RRAM-Based Analog Approximate Computing

    Boxun Li;Peng Gu;Yi Shan;Yu Wang

  • A 2.75-to-75.9TOPS/W Computing-in-Memory NN Processor Supporting Set-Associate Block-Wise Zero Skipping and Ping-Pong CIM with Simultaneous Computation and Weight Updating

    Jinshan Yue;Xiaoyu Feng;Yifan He;Yuxuan Huang

  • Spatial-Temporal Attention Res-TCN for Skeleton-Based Dynamic Hand Gesture Recognition

    Jingxuan Hou;Guijin Wang;Xinghao Chen;Jing-Hao Xue

  • FPGP: Graph Processing Framework on FPGA A Case Study of Breadth-First Search

    Guohao Dai;Yuze Chi;Yu Wang;Huazhong Yang

  • TIME: A Training-in-memory Architecture for Memristor-based Deep Neural Networks

    Ming Cheng;Lixue Xia;Zhenhua Zhu;Yi Cai

Frequent Co-Authors

Yongpan Liu
Yongpan Liu Tsinghua University
Yuan Xie
Yuan Xie Hong Kong University of Science and Technology
Meng-Fan Chang
Meng-Fan Chang National Tsing Hua University
Yu Cao
Yu Cao University of Minnesota
Yong Lian
Yong Lian York University
Xin-Jun Liu
Xin-Jun Liu Tsinghua University
Xiaojun Guo
Xiaojun Guo Shanghai Jiao Tong University
Chun Jason Xue
Chun Jason Xue Mohamed bin Zayed University of Artificial Intelligence
Jiang Xu
Jiang Xu Hong Kong University of Science and Technology

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Pursuing a degree in Electronics and Electrical Engineering offers a variety of flexible learning options tailored to different needs. For those seeking focused expertise, a competency based masters degree allows students to advance by demonstrating skills rather than time in class, making it ideal for career changers or professionals.

Military spouses and dependents often face unique challenges in education. Fortunately, there are excellent online universities for military spouses that provide flexibility and support, allowing them to pursue degrees without relocation.

If you’re eager to start soon, many online colleges starting this month offer rolling admissions and frequent start dates, enabling quick enrollment and uninterrupted progress toward your goals.

For those looking to quickly enter or upskill in the field, exploring 6 month certificate programs can be a strategic route. These programs focus on in-demand skills, opening doors to well-paying jobs in a short time frame.

Best Scientists Citing Huazhong Yang

Trending Scientists

Recently Published Articles