Weng-Fai WONG

Weng-Fai WONG is an Associate Professor in the Department of Computer Science at the National University of Singapore. His research interests include systems and networking, with a focus on embedded systems, compilers, and computer architecture. He has worked on optimizing software and applications for novel hardware such as FPGAs, GPUs, and non-volatile memory. His current research emphasizes approximate computing, including precision analysis and the use of approximate hardware accelerators for deep learning networks. He has contributed to projects such as operating system support for large memory systems and has published in top conferences and journals.

Weng-Fai Wong is an Associate Professor of Computer Science at the National University of Singapore, specializing in computer architecture, compilers, high performance computing, embedded systems, and parallel processing. His research focuses on optimizing hardware and software systems for efficiency and performance, with applications in areas such as embedded systems, neuromorphic computing, and approximate computing. He has published extensively on topics including cache design, energy-efficient algorithms, and hardware-based computation. His work explores the integration of emerging technologies like RRAM and spiking neural networks into computing systems, aiming to enhance performance while reducing energy consumption.