Technologies such as smartdust, the Internet of Things and edge intelligence have the potential to shape how our societies evolve. These technologies enable the deployment of trillions of interconnected sensors for continuous observation, with applications for health, safety, transportation and agriculture. Because these interconnected sensors operate from energy harvested from the environment—to avoid the problem of recharging or replacing trillions of batteries—their power budget is extremely limited. At the same time, these sensors perform power-hungry data collection and processing. The two requirements, ultra-low power operation with power-hungry processing capabilities, remain at odds; sensor technologies in use today require this tradeoff. Patricia Gonzalez, a recent graduate of the University of Virginia's Charles L. Brown Department of Electrical and Computer Engineering, has reconciled these two competing requirements. She introduced and developed the theoretical foundations for a novel computing paradigm that replaces the popular digital representation of data with continuous time asynchronous streams. This research earned top paper at the Institute of Electrical and Electronics Engineers Latin American Symposium on Circuits and Systems conference in February 2019. “Many aspects of asynchronous computing with streams remain unexplored, including the ultra-low power sensor architecture, the capacity to handle more data units and systems integration,†Gonzalez said. Asynchronous computing with streams requires new and complementary sensor architectures to obtain an end-to-end processing on-stream system. Gonzalez successfully defended her dissertation in July 2019, under the tutelage of her adviser Mircea R. Stan, Virginia Microelectronics Consortium Professor in electrical and computer engineering. Through her dissertation, Gonzalez has opened the door for a new area of research with many opportunities, and more challenges, for the next generation of Ph.D. students and entrepreneurs.