This page describes my research in data mining algorithms, that is, solution techniques for specific tasks in data analysis. Unlike the area of applications, where multiple challenges often have to be addressed simultaneously, a focus on the algorithms enables me to consider, in isolation, each of the many challenges encountered in real applications. I can create computationally efficient solutions that are appropriate to the size of the data, can process the variation in the data, and are robust to the settings of parameters of the algorithms. It is also an opportunity to advance the state of the art in analysis algorithms.
More details on my research in algorithms is available on the following pages:
- Surrogates and sampling for simulations
- Intelligent sampling
- Regression with small data sets
- Interpreting the solution to inverse problems
- Independent-block Gaussian process
- Compressing unstructured simulation data
- Intelligent exploration of large-scale data
- Analysis of time series data from sensors
- Dimension reduction for scientific applications
- ASPEN