World's Best Scientists 2026 revealed!
Philip H. W. Leong

Philip H. W. Leong

D-Index & Metrics

Computer Science

D-Index
47
Citations
8579
World Ranking
6516
National Ranking
205

Electronics and Electrical Engineering

D-Index
45
Citations
8061
World Ranking
3560
National Ranking
116

Overview

Philip H. W. Leong is affiliated with the University of Sydney in Australia, contributing extensively to the fields of computer science and engineering. Their research spans several key subfields, including electrical and electronic engineering, artificial intelligence, computer vision and pattern recognition, signal processing, and computer networks and communications.

The scientist's work encompasses a range of topics characterized by a focus on signal processing, neural networks, VLSI design, and wireless communications. Notable areas covered include:

  • Blind Source Separation Techniques
  • Wireless Signal Modulation Classification
  • VLSI and Analog Circuit Testing
  • Cooperative Communication and Network Coding
  • Advanced Neural Network Applications
  • Image and Video Quality Assessment
  • Low-power high-performance VLSI design

Recent publications of Philip H. W. Leong include:

  • "NITI: Training Integer Neural Networks Using Integer-Only Arithmetic", 2022, IEEE Transactions on Parallel and Distributed Systems
  • "Interpolating high granularity solar generation and load consumption data using super resolution generative adversarial network", 2021, Applied Energy
  • "On-Device Saliency Prediction Based on Pseudoknowledge Distillation", 2022, IEEE Transactions on Industrial Informatics
  • "Nonlinear retinal response modeling for future neuromorphic instrumentation", 2020, IEEE Instrumentation & Measurement Magazine
  • "Wireless Signal Representation Techniques for Automatic Modulation Classification", 2022, IEEE Access

Philip H. W. Leong frequently collaborates with a variety of co-authors, including David Boland, Carol Jingyi Li, Binglei Lou, S A Rasoulinezhad, and Craig Jin. These collaborations highlight their engagement within a network of researchers in overlapping domains of study.

Their work has been published in several venues, with notable frequent appearances in:

  • ACM Transactions on Reconfigurable Technology and Systems
  • arXiv (Cornell University)
  • IEEE Transactions on Parallel and Distributed Systems
  • Applied Energy
  • IEEE Transactions on Industrial Informatics

Philip H. W. Leong's research integrates multidisciplinary approaches that facilitate advances in computing architectures, neural network methodologies, and signal processing systems. This intersection supports developments in both theoretical frameworks and practical applications relevant to modern technology challenges.

Best Publications

  • FINN: A Framework for Fast, Scalable Binarized Neural Network Inference

    Yaman Umuroglu;Nicholas J. Fraser;Giulio Gambardella;Michaela Blott

  • A laser-micromachined multi-modal resonating power transducer for wireless sensing systems

    Neil N.H. Ching;H.Y. Wong;Wen J. Li;Philip H.W. Leong

  • Gaussian random number generators

    David B. Thomas;Wayne Luk;Philip H.W. Leong;John D. Villasenor

  • The nature and distribution of errors in sound localization by human listeners

    Simon Carlile;Philip Leong;Stephanie Hyams

  • A hardware Gaussian noise generator using the Box-Muller method and its error analysis

    D.-U. Lee;J.D. Villasenor;W. Luk;P.H.W. Leong

  • Method and system for automatically classifying intracardiac electrograms

    Philip H. W. Leong;Marwan A. Jabri

  • Compact FPGA-based true and pseudo random number generators

    K.H. Tsoi;K.H. Leung;P.H.W. Leong

  • Active temporal multiplexing of indistinguishable heralded single photons

    Chunle Xiong;X. Zhang;Z. Liu;Z. Liu;Matthew J. Collins

  • A Smith-Waterman systolic cell

    C. W. Yu;K. H. Kwong;K. H. Lee;P. H. W. Leong

  • A Hybrid CMOS-Memristor Neuromorphic Synapse

    Mostafa Rahimi Azghadi;Bernabe Linares-Barranco;Derek Abbott;Philip H. W. Leong

  • Dynamic voltage scaling for commercial FPGAs

    C.T. Chow;L.S.M. Tsui;P.H.W. Leong;W. Luk

  • A hardware Gaussian noise generator using the Wallace method

    Dong-U Lee;W. Luk;J.D. Villasenor;Guanglie Zhang

  • SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks

    Julian Faraone;Nicholas Fraser;Michaela Blott;Philip H.W. Leong

  • FPGA implementation of a microcoded elliptic curve cryptographic processor

    K.H. Leung;K.W. Ma;W.K. Wong;P.H.W. Leong

  • Reconfigurable acceleration for Monte Carlo based financial simulation

    G.L. Zhang;P.H.W. Leong;C.H. Ho;K.H. Tsoi

  • A microcoded elliptic curve processor using FPGA technology

    P.H.W. Leong;I.K.H. Leung

  • Methods for spherical data analysis and visualization.

    Philip Leong;Simon Carlile

  • Ultralow-Power Alcohol Vapor Sensors Using Chemically Functionalized Multiwalled Carbon Nanotubes

    M.L.Y. Sin;G.C.T. Chow;G.M.K. Wong;Wen Jung Li

  • Compact and reconfigurable silicon nitride time-bin entanglement circuit

    C. Xiong;X. Zhang;A. Mahendra;J. He

  • Writing system with camera

    Guanglie Zhang;Guangyi Shi;Yilun Luo;Heidi Yee Yan Wong

Frequent Co-Authors

Wayne Luk
Wayne Luk Imperial College London
Wen J. Li
Wen J. Li City University of Hong Kong
Steven J. E. Wilton
Steven J. E. Wilton University of British Columbia
Benjamin J. Eggleton
Benjamin J. Eggleton University of Sydney
Peter Y. K. Cheung
Peter Y. K. Cheung Imperial College London
Eryk Dutkiewicz
Eryk Dutkiewicz University of Technology Sydney
Dagan Feng
Dagan Feng University of Sydney
Qiang Xu
Qiang Xu Chinese University of Hong Kong
Zongwen Liu
Zongwen Liu University of Sydney
Derek Abbott
Derek Abbott University of Adelaide

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 opens a range of career opportunities, but many students also explore related fields to enhance their skills or shift their focus. For example, a master's in instructional design can be an excellent path for those interested in educational technology and training development within engineering industries.

Online education options are more flexible than ever. Programs emphasizing competency based degrees and programs allow students to progress at their own pace by demonstrating mastery in key areas. This is ideal for working professionals balancing careers with further education.

Additionally, several schools cater specifically to the unique needs of military families. Discovering online colleges for military spouses can provide critical support and flexible learning environments for those managing frequent relocations or deployments.

For students eager to start their studies without delay, many online colleges that start immediately offer weekly start dates, reducing wait times and allowing for a quicker entry into advanced training or new career paths.

Best Scientists Citing Philip H. W. Leong

Trending Scientists