Expertise: Database systems, systems for big data and machine learning

For Jia Zou, her passion for scientific research was solidified the day she entered an international mathematical contest in modeling with two college classmates. The competition, sponsored by the Consortium for Mathematics and Its Applications, required each team to build a mathematical model to investigate a real-world issue.

“We won a meritorious prize, and working with a great team on an exciting problem ushered me into a lifelong love for research,” say Zou.

After earning her doctoral degree, Zou worked as a researcher at IBM Research-China.

“During that time, I had the opportunity to talk to IBM customers from various industries such as telecom, banking, internet companies and so on,” says Zou. “All the real-world use cases I’ve learned formed a clear vision for the future of data-intensive systems.” 

Zou then joined Rice University as a research scientist.

“During my time at Rice, several research papers have been published in VLDB and SIGMOD, which are the two flagship conferences in the big data research community, including an honorable mention in VLDB 2019. The recognition received for our research products further encourages me to stay.” says Zou.

At ASU, Zou’s research will focus on database systems and systems for big data and machine learning.

“I choose this area for my research because data is collected at a sharply rising speed in this more and more digitally connected world,” says Zou. “The total volume of data collected on Earth will reach 44 zettabytes by next year (one zettabyte equals 1 trillion gigabytes). Every industry needs to learn how to swim in such an ocean of data, and I want to help them.”

This semester, Zou will focus her research on providing deterministic performance for machine learning systems and applications.

“That means a user can expect the completion time of their machine learning applications falls in a pre-specified performance envelope,” says Zou. “I’m excited, because this is super important in emerging internet of thing applications, such as automatic car driving and health care, to avoid loss of lives and money due to delayed response.”