Department of Computer Science and the College
Eric Jonas’s research centers on using machine learning and scalable computing to make better measurements about the universe. Much of science is still data-limited, but new and emerging measurement techniques can dramatically accelerate the ability to understand and interpret the natural world. Jonas has focused on applications from the smallest phenomena at the center of an atom (nuclear spectroscopy) to systems as large as the sun. He is especially interested in how computational models can guide measurement and what they can reveal about complex systems (especially biological ones). For example, using the popular analogy of brains to computers, he tested the analytical techniques of neuroscience by applying those techniques to a microprocessor, research that was featured in The Economist.
His work has been published in eLife, PLOS Computational Biology, the Journal of Machine Learning Research, Solar Physics, and the Journal of Cheminformatics, as well at conferences such as the ACM Symposium on Cloud Computing (SoCC), International Conference on Artificial Intelligence and Statistics (AISTATS), and Conference on Neural Information Processing Systems (NeurIPS). He was named one of the top rising stars by the Defense Advanced Research Projects Agency (DARPA).
Jonas received a PhD in neuroscience, as well as master’s and bachelor’s degrees in electrical engineering and computer science, and a bachelor’s degree in brain and cognitive sciences, all from the Massachusetts Institute of Technology. Prior to joining the University of Chicago, he was a postdoctoral researcher at the Center for Computational Imaging and RISELab at the University of California, Berkeley.
Photo credit: Vimal Bhalodia