Still settling into her sparsely decorated office on the third floor of the Engineering Research Center, and patiently awaiting the outfitting of a laboratory, Peipei Zhou has already immersed herself into Brown Engineering’s collaborative culture. A quick look at her biography says she is an Assistant Professor of Engineering and director of the Customized Computer Architecture Research Lab, but a few minutes spent with her tells you her reach is far beyond what one would associate with a young faculty member.
Customized computer architecture is the buzzword phrase for Zhou’s work. Her most recent endeavor involves a chiplet system for autonomous cars and includes collaboration with researchers from Wayne State University and the University of Delaware. “Potentially, we can do much better computing with lower latency on autonomous driving,” she explains. “Because in an autonomous driving vehicle, as you know, the latency constraint is very strict, like a millisecond. One millisecond is a very strict deadline. If that deadline is missed, it could have a very catastrophic result.”
That is just one of the customized applications Zhou feels passionately about. She also has ongoing collaborations for projects involving precision medicine and semiconductor devices, and points to the open letter signed by 13 women university presidents and deans of engineering from six institutions (Brown’s Christina Paxson and Tejal Desai among them) in support of the CHIPS and Science Act as one of the top reasons she landed on College Hill.
Zhou received her bachelor’s degree in electrical and computer engineering from Southeast University, Chien-Shiung Wu Honor College in 2012, a master’s in electrical and computer engineering from the University of California, Los Angeles in 2014, and a Ph.D. in computer science from UCLA in 2019. It was at UCLA where she studied with Computer Science Professor Jason Cong, an academic giant in Field-Programmable Gate Array (FPGA), and electronic design automation technology.
Her undergraduate work allowed her to choose her major in what Zhou says was strikingly similar to the way Brown’s Open Curriculum works. “We could personalize a course plan after sophomore year and that is when I made the decision that I wanted to focus on the hardware and software interface, and then how to build and program new computing systems.” The further training and continuation for the next seven years as a Ph.D. student in computer science was spent building more expertise and exposure to real-world applications, she said.
“At that time, we worked on human genome processing and medical imaging applications. We built computing infrastructure that increased the computing process of sequencing the whole human genome from about two days down to 30 minutes, which has since been deployed in UCLA’s Institute for Precision Health.
“Those are the things I want to be able to do. That was my Ph.D. thesis,” she said. More broadly, her thesis investigated modeling and optimization for customized computing at chip-level, node-level, and cluster-level, using the acceleration of the widely used Genome Analysis Toolkit by focusing on its algorithm and hardware co-design as one example.