Current and Recent Research Projects in the Smyth DataLab Group

Projects in our research group span a variety of topics involving fundamental research on basic aspects of machine learning, including predictive modeling, deep learning, Bayesian methods, time-series and sequence modeling, image and spatial data analysis, text analysis, and more. Our group has a long and successful history of developing new ideas and algorithms that lie at the intersection of machine learning and statistics. We are also involved in numerous applications, working with expert collaborators to apply machine learning and statistical techniques to address real-world problems across a variety of important application areas in medicine, science, engineering, the social sciences, and business.

PhD students interested in joining our Datalab research group should apply to either the Computer Science or Statistics PhD programs at UC Irvine. Students with strong quantitative backgrounds are particularly encouraged to apply (with undergraduate or Master's degrees in Computer Science, Electrical Engineering, Statistics, Mathematics, Physics, or related areas).

Below are some examples of current and recent projects in our group. The list below is illustrative rather than exhaustive - we have broad interests in our research group and are often exploring new ideas and projects that are not listed below.