Riddhi brings industry and academic experience in working on quantum error mitigation, quantum error correction, and quantum control theory to enable quantum computing demonstrations on near-term hardware. She investigates the feasibility of combining error mitigation and error correction techniques with quantum machine learning algorithms at the University of Queensland. With Sally Shrapnel and partnering with the Queensland Digital Health Center (QDHeC), Riddhi analysed the operational robustness of quantum machine learning, with an eye to digital health use-case discovery and testing. Prior to this, she worked on execution of dynamic circuits for error mitigation and quantum error correction applications at IBM Quantum (US) for three years. Her work resulted in three patents and being recognised as one of IBM Research’s Top Technical Contributors in 2023 globally. She has also designed classical algorithms for noise filtering and prediction for trapped ions at the Quantum Control Laboratory in the University of Sydney, winning ARC EQUS inaugural Director’s Medal in Australia in 2019.