Dr. Mao’s research interests mainly focus on the fields of cloud computing, virtualization, resource management, data-intensive platforms, quantum cloud and system optimization.
We develop algorithms to improve the performance of existing systems and propose novel system architectures to address practical issues in industry. Specifically, Dr. Mao’s investigate the following research problems.
Cloud management: we build efficient cluster management algorithms for virtualized computing platforms, such as Docker and Kubernetes, to efficiently schedule the resources and improve the performance.
Domain-specific systems: we analyze the characteristics of specific applications, such as Deep learning (Tensorflow / Pytorch) and Big data (Hadoop / Spark), and design novel algorithms to achieve system scalability.
Quantum-based systems: we develop algorithms based on the utilize quantum bits (qubits) to improve the classic applications, such as deep neural networks.