REU Site: Summer Undergraduate Program in Engineering Research at Berkeley (SUPERB): Collecting and Using Big Data for the Public Good

University Of California-Berkeley, Berkeley CA

Investigators

Abstract

It is evident to all of us that the widespread and growing availability of vast amounts of real-time data presents both a tremendous opportunity to improve our understanding of the world and make better automated decisions, as well as a great technical challenge to collect, communicate and process this data efficiently and reliably. Leading researchers in Electrical Engineering and Computer Science will mentor undergraduate students on their proposed REU projects. Potential impacts range from more efficient sensor networks, to improved wireless access to the data they produce, to better human robot interaction, to better analysis of medical data from microscopes, and even helping prevent nuclear war. The project seeks to address a multitude of societal problems that can be examined by collecting and using big data while inspiring students to dedicate themselves to this work. The project is committed to exposing a diverse group of undergraduate researchers that will expand the impact of this project and the engineering research pipeline. At the conclusion of the program, participants will be proficient in using big data to solve societal problems that have direct impacts on their communities. The goal of the Summer Undergraduate Engineering Research project in the Electrical Engineering and Computer Sciences Department is to prepare and motivate a group of diverse competitive candidates for graduate student. The focus of the REU site is electrical engineering and computer science to support collecting and using big date for the public good. Students spend nine weeks during the summer working on high caliber research projects addressing technical challenges arising in collecting, communicating and processing the vast amounts of data becoming available both efficiently and reliably. This project covers the entire range of challenges and opportunities, from better sensor networks to collect this data more efficiently; to improved wireless resource management to move the data; to machine learning techniques for processing the images, including from microscopes, that make up much of the new data; to designing robots that can learn to interact better with humans based on the data they collect; to better enforcement of the Comprehensive Nuclear Test Ban Treaty by analyzing seismic data used to detect underground nuclear tests. The project will have research contributions in areas such as communications and networking, human computer interaction, machine learning, robotics, scientific computing and visualization.