"Getting early-career support can be a make-or-break moment for a young scholar," said Paul L. Joskow, President of the Alfred P. Sloan Foundation. "In an increasingly competitive academic environment, it can be difficult to stand out, even when your work is first rate. The Sloan Research Fellowships have become an unmistakable marker of quality among researchers. Fellows represent the best-of-the-best among young scientists."
Prof. Cafarella's research has advanced the practice and application of big data. In particular, he has built software systems for crucial data management challenges such as information extraction, database integration, and feature engineering.
Prof. Cafarella has applied these systems to a number of problems, especially in the social sciences. He used data from social media streams to accurately predict government statistics, such as unemployment rates, without the overhead of surveys and data gathering that is traditionally employed. More recently, he contributed toward the DeepDive information extraction system and applied it to the problem of illegal sex trafficking; by analyzing online text sources, this effort generated information and tools that can aid law enforcement.
In previous work, he and Doug Cutting developed Hadoop, an open-source software framework for distributed storage and processing of very large data sets on computer clusters. Hadoop is currently employed by many research groups and large companies, including Facebook, Yahoo, Twitter, and more than half of the Fortune 50.Prof. Cafarella received his PhD in Computer Science from the University of Washington in 2009 and joined the faculty at Michigan that year. He has published extensively in venues such as SIGMOD, VLDB, and elsewhere. He received an NSF CAREER award in 2011 and was named a Morris Wellman Faculty Development Professor in 2016. He is affiliated with the Software Systems Lab and the Michigan Institute for Computational Discovery & Engineering (MICDE).
Prof. Lee's research interests lie in machine learning and its applications to artificial intelligence. In particular, he focuses on deep learning and representation learning, which aims to learn an abstract representation of the data by a hierarchical and compositional structure. Specific application areas include computer vision, audio recognition, robotics, text modeling, and healthcare.
Prof. Lee is currently developing deep learning algorithms aimed at disentangling variations from complex data, and the development of a graphical model with deep representations that can model complex dependencies between output variables.
Prof. Lee received his PhD in Computer Science from Stanford University in 2010 and joined the faculty at Michigan that year. He has served as a guest editor of IEEE TPAMI Special Issue on Learning Deep Architectures, as well as area chairs of ICML, NIPS, ICCV, AAAI, IJCAI, and ICLR. He was named one of AI's 10 to Watch by IEEE Intelligent Systems in 2013 and received an NSF CAREER award in 2015. He is a recent recipient of a Google Faculty Research Award and was named a Morris Wellman Faculty Development Professor in 2016. He is affiliated with the Artificial Intelligence Lab and the Michigan Institute for Data Science (MIDAS).
About the Sloan Research Fellowship
The Sloan Research Fellowships seek to stimulate fundamental research by early-career scientists and scholars of outstanding promise. These two-year fellowships are awarded yearly to 126 researchers in recognition of distinguished performance and a unique potential to make substantial contributions to their field.
Posted: February 24, 2016