John’s research addresses the design of custom hardware for embedded/edge signal processing and machine learning applications – particularly Field Programmable Gate Array (FPGA). It sits at the intersection of advanced algorithm, compiler/synthesis technology and custom hardware architectures. He is particularly interested in novel computational paradigms, including dataflow, neuromorphic and quantum computing.