Wang received her PhD in statistics from the University of Michigan at Ann Arbor in 2019, and joined the faculty at UC Berkeley soon thereafter, in fall of the same year. Wang’s research applies new machine-learning methods to massive genetic data sets to show that different lifestyle interventions work better for different people. Her research can also be used to to identify more effective COVID-19 treatments.
“Jingshen’s work is important because it tackles head-on some of the hardest challenges we must face if we are to transform the potential of big data into meaningful improvements in health,” said Maya Petersen, biostatistics division head. “Her work develops new approaches to improve personalized health interventions and to learn more from massive data streams such as MHealth (mobile health, such as smart phone apps) sensor data or even text message data.”
Wang, who is 29 years old, has impressed her colleagues with her novel research despite her young age. “I really don’t know how she has accomplished so much at a young age,” said Petersen, “beyond the obvious—amazing talent and motivation!”
“I feel really honored, humbled and (to some degree) surprised to receive this award,” said Wang, who also thanked her colleagues at Berkeley Public Health for their support. “As a statistician, I never expected one day that my work would be recognized by a wider audience. Having this award boosts my confidence that we (statisticians) can be appreciated by the general public as long as we clearly communicate our ideas.”