James Davis is a Research Fellow in the Department of Electrical and Electronic Engineering's Circuits and Systems group at Imperial College London.
His research interests include:
- Runtime monitoring of digital electronic hardware
- Computer arithmetic
- Neural network inference
- Fault tolerance, reliability and lifetime extension
- Self-adaptive systems
- Reconfigurable computing
- Heterogeneous and embedded systems.
James serves on the technical programme committees of the four top-tier reconfigurable computing conferences (FPGA, FCCM, FPL and FPT) and is a multi-best paper award recipient. He is a Member of the IEEE and ACM.
et al., 2021, Digit Stability Inference for Iterative Methods Using Redundant Number Representation, Ieee Transactions on Computers, Vol:70, ISSN:0018-9340, Pages:1074-1080
et al., Logic Shrinkage: Learned FPGA Netlist Sparsity for Efficient Neural Network Inference, ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, ACM
et al., 2021, Enabling Binary Neural Network Training on the Edge, International Workshop on Embedded and Mobile Deep Learning (EDML), ACM, Pages:37-38
et al., Enabling Binary Neural Network Training on the Edge, Workshop on Binary Networks for Computer Vision