My research interests are centered around Computer Systems. I am currently focusing on storage and persistent memory technologies, with an emphasis on their impact on the way we manage large-scale data for emerging workloads in Data Science and the Internet of Things.

I completed my PhD in Computer Science at EPFL/the University of Sydney in 2020, advised by Prof. Willy Zwaenepoel. My dissertation research was on the design and implementation of efficient key-value stores for future hardware and performance requirements.

For decades, Moore’s Law and its partner Dennard Scaling have driven technology trends that have enabled exponential performance improvements in computer systems at manageable power dissipation. With the slowing of Moore/Dennard improvements, designers have turned to a range of approaches for extending scaling of computer systems performance and power efficiency. Unfortunately, these scaling gains come at the expense of degraded hardware-software abstraction layers, increased complexity at the hardware-software interface, and increased challenges for software reliability, interoperability, and performance portability. My work explores the way forward for computer systems designers in this “Post-ISA” era of shifting abstractions. My group looks hardware and software design issues for specialization/heterogeneity and methods for formal verification. We are also increasingly focused on the hardware/software systems issues of Quantum Computing.

Rujia Wang joined Illinois Institute of Technology in Fall 2018. She earned her Ph.D. and M.S degree from Electrical and Computer Engineering Department at the University of Pittsburgh and her B.E. from Zhejiang University. Her research experience spans across multiple areas in computer engineering, including novel memory architecture, secure computing architecture, system reliability, and high-performance computing, and her work has been published in top conferences in computer architecture area.