In today’s environment, computational science, machine learning and data analytics are becoming more prevalent, useful and important. There’s a growing need for learning and data analysis algorithms that can assess and utilize large sets of data for decision-making processes. Whether those processes are being used to help machines determine the funniest cartoon captions, better predict an individual’s risk for Alzheimer’s, help you choose a beer you’ll like, or design safer and more reliable driverless vehicles, machine learning and data science are explosively growing areas.
Yet, there’s so much we still don’t know. That’s why the University of Wisconsin-Madison College of Engineering’s Grainger Institute for Engineering has established a research focus area, called machines, algorithms and data, to continue building the mathematical and computational foundations of machine learning and data science. Robert Nowak, the McFarland-Bascom Professor in electrical and computer engineering, is leading the charge.
“I’m excited for Rob to lead the machines, algorithms and data focus area,” says Dan Thoma, director of the Grainger Institute for Engineering. “His technical expertise, his passion, his ability to work across all disciplines with data—it’s rare that you find all that talent in one person.”
Machines, algorithms and data research complements all the activities within the institute, from biomanufacturing and smart and connected healthcare to advanced manufacturing and materials discovery. And beyond basic research, there’s endless potential for industrial, commercial, governmental and societal applications.
“I’m always excited by a new challenge,” says Nowak. “A lot of my work happens when someone raises a question—a student, myself or a collaborator—and I’m just stumped. In this area of algorithms and data, there are more mysteries than there are answers right now.”
He’s also looking forward to capitalizing on the magnitude of talent across the university and within the College of Engineering. “The college has hired some fantastic new assistant professors, the Grainger Institute for Engineering has brought in a lot of young talent, and we have ongoing collaborations with talent in computer science, mathematics and statistics,” he says.
Nowak posits that we’re at the beginning of a potentially significant change in the way we use machines, algorithms and data. “It’s one thing to have machine learning, artificial intelligence and data science driving the products online retailers are recommending to you; it’s another thing to have it driving your car,” he says.
For him, the ultimate challenge will be making machine learning safer and more reliable no matter the application.