I am interested in parallel and heterogeneous architectures and application-specific accelerators, and how we can design and program them to continue improving application performance and efficiency in the face of limits to frequency and power scaling.

I am an Assistant Professor in the Computer Science and Engineering Department at University of California, San Diego. My research spans and stretches the boundary between computer architecture and system software, with an emphasis on memory and storage systems and domain-specific acceleration. I am particularly interested in architecting emerging memory technologies (e.g., nonvolatile memories and 3D-stacked memory) into future data centers and edge computing systems that execute various applications, e.g., machine learning, big-data analytics, smart home, and smart transportation. I am also interested in developing deep learning to help computer systems design and programming.

Evey Liu recently finished her undergraduate study at the University of Waterloo for Computer Engineering. She will begin graduate school at the University of Toronto with supervisor Natalie Enright Jerger in January 2019. She is passionate about generic computer architecture and is open to explore different specializations within the field.

I am broadly interested in hardware security. I am working on designs of new Physically Unclonable Functions (PUFs), leveraging physical properties of hardware for new cryptographic and security applications, and security verification of processor architectures.