World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
37
Citations
4518
World Ranking
5204
National Ranking
763

Best Publications

  • Design of Approximate Radix-4 Booth Multipliers for Error-Tolerant Computing

    Weiqiang Liu;Liangyu Qian;Chenghua Wang;Honglan Jiang

  • A Retrospective and Prospective View of Approximate Computing [Point of View}

    Weiqiang Liu;Fabrizio Lombardi;Michael Shulte

  • Design and Evaluation of Approximate Logarithmic Multipliers for Low Power Error-Tolerant Applications

    Weiqiang Liu;Jiahua Xu;Danye Wang;Chenghua Wang

  • Are QCA cryptographic circuits resistant to power analysis attack

    Weiqiang Liu;S. Srivastava;Liang Lu;M. O'Neill

  • Design rules for Quantum-dot Cellular Automata

    Weiqiang Liu;Liang Lu;Maire O'Neill;Earl E. Swartzlander

  • Design and Analysis of Majority Logic-Based Approximate Adders and Multipliers

    Weiqiang Liu;Tingting Zhang;Emma McLarnon;Maire OrNeill

  • A Flip-Flop Based Arbiter Physical Unclonable Function (APUF) Design with High Entropy and Uniqueness for FPGA Implementation

    Chongyan Gu;Weiqiang Liu;Yijun Cui;Neil Hanley

  • Design and Analysis of Approximate Redundant Binary Multipliers

    Weiqiang Liu;Tian Cao;Peipei Yin;Yuying Zhu

  • High Performance CNN Accelerators Based on Hardware and Algorithm Co-Optimization

    Tian Yuan;Weiqiang Liu;Jie Han;Fabrizio Lombardi

  • Approximate Designs for Fast Fourier Transform (FFT) With Application to Speech Recognition

    Weiqiang Liu;Qicong Liao;Fei Qiao;Weijie Xia

  • Hybrid Low Radix Encoding-Based Approximate Booth Multipliers

    Haroon Waris;Chenghua Wang;Weiqiang Liu

  • Design and Implementation of an Approximate Softmax Layer for Deep Neural Networks

    Yue Gao;Weiqiang Liu;Fabrizio Lombardi

  • On the Design of Approximate Restoring Dividers for Error-Tolerant Applications

    Linbin Chen;Jie Han;Weiqiang Liu;Fabrizio Lombardi

  • Design and Analysis of Energy-Efficient Dynamic Range Approximate Logarithmic Multipliers for Machine Learning

    Peipei Yin;Chenghua Wang;Haroon Waris;Weiqiang Liu

  • Design of Approximate Unsigned Integer Non-restoring Divider for Inexact Computing

    Linbin Chen;Jie Han;Weiqiang Liu;Fabrizio Lombardi

  • Intellectual Property Protection for Deep Learning Models: Taxonomy, Methods, Attacks, and Evaluations.

    Mingfu Xue;Yushu Zhang;Jian Wang;Weiqiang Liu

  • A machine learning attack resistant multi-PUF design on FPGA

    Unknown

  • Hybrid Partial Product-based High-Performance Approximate Recursive Multipliers

    Haroon Waris;Chenghua Wang;Weiqiang Liu;Jie Han

  • A Modeling Attack Resistant Deception Technique for Securing Lightweight-PUF-Based Authentication

    Chongyan Gu;Chip-Hong Chang;Weiqiang Liu;Shichao Yu

  • Design and evaluation of an approximate Wallace-Booth multiplier

    Liangyu Qian;Chenghua Wang;Weiqiang Liu;Fabrizio Lombardi

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