For his work exploring ways to teach computers how to learn from their past behavior, Jonathan Appavoo, a College of Arts & Sciences assistant professor of computer science, has been awarded a Faculty Early Career Development Award from the National Science Foundation (NSF). The award—valued at nearly $600,000—will support his research and teaching efforts in operating systems, in particular his project involving programmable smart machines.

The main challenge Appavoo seeks to address in his project is this: faster computers have enabled advances in science, commerce, and daily life. Unfortunately, computers have also become complex and more difficult to program efficiently, threatening further advances.

Perhaps, posits Appavoo, we can draw upon biologically inspired learning techniques in designing a new model of hybrid computer, a programmable smart machine, which learns from its past behavior to automatically improve its performance without the burden of more complex programming. Specifically, his work explores the addition of a smart memory to a computer, which gives it the ability to learn, store, and exploit patterns in past execution.

Appavoo says he’s long been fascinated by computers, “because they somehow seemed to mimic and reflect our own abilities.” As he studied them in greater depth, he realized “that while they are fascinating machines, their ‘human’ qualities are largely achieved by smoke and mirrors,” he says. “That being said, their ability to be programmed to do arbitrary tasks over and over again at very high speeds is incredibly powerful.”

The father of two young children, Appavoo says he is keenly aware of “our limited human ability to be programmed and directed, but also of our incredible capacity to learn and improve based on experience.” His research is trying to answer the question of whether there is a way to combine these abilities to “yield machines that can both be programmed and also intrinsically improve by taking advantage of their size and experience.” In other words, he says, can you create a new kind of “programmable smart machine that improves with its size and experience?”

The NSF grant, valued at $595,000 and to be awarded over five years, will allow him to “explore the possibility of constructing hybrid computing systems that behave as programmed but transparently learn and automatically improve their operation by studying if and how a computer system can integrate learning mechanisms into their core execution model,” he says.

“The work John is doing in computer science is one more example of the leading-edge research that is going on in the College of Arts & Sciences,” says Dean Virginia Sapiro. “I am excited to see John join the ranks of our young faculty members who have earned the distinction of winning the NSF Early Career Award.”

The NSF’s Faculty Early Career Development Awards are given to support junior faculty “who exemplify the role of teacher-scholars through outstanding research, excellent education, and the integration of education and research within the context of the mission of their organizations.”

Appavoo says the NSF award will allow him to move his research to the next stage. “This work began over a decade ago,” he says, “and it epitomizes the kind of exploration that drew me to science and has motivated my career to this point. It is very exciting to now have the resources to explore a different kind of computer that incorporates a biologically motivated mechanism into its inner workings.”