Google recognizes URI Computer Engineering professor with Faculty Research Award

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Bin Li
Google Faculty Research Award Winner: Bin Li, assistant professor of electrical, computer and biomedical engineering at the University of Rhode Island’s College of Engineering
(Photo courtesy: Bin Li)

KINGSTON, R.I. – March 6, 2020 – They are created to make our lives easier – find us a cheaper price on a gallon of gas, warn us of traffic or an accident in our path and direct us to our location more quickly, locate the best value on milk and eggs – but in the digital age, crowd-learning apps are only as good as the usefulness of the information they collect and the speed with which they share it.

Bin Li, an assistant professor of electrical, computer and biomedical engineering at the University of Rhode Island’s College of Engineering, is all too familiar with the drawbacks of these types of crowd-learning apps and is working to make them better. Li was recently one of a select group of academics worldwide to be recognized with a Google Faculty Research Award for his research in this area. In addition to funding tuition for a research assistant, the award program also facilitates collaboration with Google researchers.

The highly competitive program supports world-class research in computer science, engineering and related fields at academic institutions around the world. This year, Google received more than 900 proposals from over 330 universities located in about 50 countries. After an extensive review process involving more than 1,100 reviewers across Google, about 15% of proposals received funding.

“It’s exciting to have this research recognized,” said Li. “We look forward to developing a relationship and sharing some of our expertise with researchers at Google in order to move this project forward.” Li submitted the proposal along with Jia Liu, an assistant professor of computer science and electrical and computer engineering at Iowa State University.

Li and Liu join researchers from institutions such as Carnegie Mellon University, Stanford University, the Massachusetts Institute of Technology and the University of Texas at Austin who are conducting research across a range of areas such as machine learning, systems, human computer interaction and more.

“The goal is to make these applications more efficient by incentivizing users to provide real-time, accurate information,” said Li. “But it doesn’t end there, the best crowd-learning apps not only take into account the age of the information submitted but an overall assessment of other environmental factors that come into play in order to provide end users with the timely and accurate information necessary to make their lives easier.”