Philip Leong

Professor of Computer Systems

University of Sydney

Australia

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Philip Leong is a Professor of Computer Systems at The University of Sydney, Australia. His research areas include FPGA-based computing, deep learning frameworks, and energy-efficient federated learning. Recent publications focus on advancing network coding, real-time analysis methods, and scalable accelerators for various computational tasks.

Philip Leong

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Articles (16)

FPGA-based Block Minifloat Training Accelerator for a Time Series Prediction Network

A Physics-Inspired Deep Learning Framework With Polar Coordinate Attention for Ptychographic Imaging

Toward High-Performance Network Coding: FPGA Acceleration With Bounded-Value Generators

Highly-Parallel CNN Accelerator for RepVGG-like Network Training on FPGAs

S$^{3}$CA: A Sparse Strip Spectral Correlation Analyzer

FedOrbit: Energy Efficient Federated Learning for Orbital Edge Computing Using Block Minifloat Arithmetic

Fixed-point FPGA Implementation of the FFT Accumulation Method for Real-time Cyclostationary Analysis

fSEAD: A Composable FPGA-based Streaming Ensemble Anomaly Detection Library

A Scalable Systolic Accelerator for Estimation of the Spectral Correlation Density Function and Its FPGA Implementation

Efficient Radius Search for Adaptive Foveal Sizing Mechanism in Collaborative Foveated Rendering Framework

Performance Analysis and Optimal Design of BATS Code: A Hardware Perspective

On-Device Saliency Prediction Based on Pseudoknowledge Distillation

NITI: Training Integer Neural Networks Using Integer-Only Arithmetic

FPGA Architecture Exploration for DNN Acceleration

Wireless Signal Representation Techniques for Automatic Modulation Classification

Interpolating high granularity solar generation and load consumption data using super resolution generative adversarial network

Collaborators (4)

Craig Jin

Shuaiwen Song

Ivan Lee

David Boland

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