2019 Ph.D. graduate Patricia Gonzalez and her advisor Mircea Stan detailed a signal processing algorithm for asynchronous computing—an approach that mimics neural networks to continually parse and transmit bytes of information—in a paper that earned Gonzalez a top student paper award at IEEE's Latin American Symposium on Circuits and Systems. They then addressed the theoretical foundations of asynchronous computing, earning a best paper award at the November 2019 Asilomar Conference on Signals, Systems and Computers. Asynchronous computing allows sensors to process information while using very low power. READ MORE.