Math/Stats Colloquium: Lisa Bramer
Speaker: Lisa Bramer, a a team lead for the Data science and Biostatistics group within the Biological Sciences Division at Pacific Northwest National Laboratory. Lisa’s current research is focused on the application and development of statistical and machine learning methods for biological data, particularly mass spectrometry omics data and streaming data analytics. She is particularly interested in exploratory data analysis and visualization for big data, data integration, and machine learning (particularly when multiple heterogeneous data sources are available), and development of robust software packages for biological data processing.
Title: Datasets Of Unusual Size and Other Interesting Problems at a National Laboratory
Abstract: The critical first step in analyzing or modeling data is visualization and exploration to assess data quality and the potential relationships between variables. The size and complexity of data are often the main factors that pose challenges to effective exploration. We will discuss a highly scalable framework for visualization of big data. In this talk, we discuss and demonstrate how it can be implemented on datasets from varied application areas such as multi-omics biological data, location tracking time series from sports data, and others.