In no particular order, these are some of the projects with which I am either currently involved or have been recently involved:
  • Clu
    • A computational cluster designed to support a cloud environment, which, in turn, support multiple machine learning/data mining environments.
    • This system supports two research thrusts: distributed machine learning evaluations and digitial forensics on Big Data platforms.
    • Project Website
  • Anomaly Detection
    • First, how can we use existing machine learning methods to detect and/or remediate anomalies?
    • Second, what changes need to be made to existing algorithms and/or what new algorithms need to be created to improve the ability to detect and remediate anomalies?
  • Multi-Layer Vector Space (MLVS) (a novel sequence representation)
    • We are looking at how this can be used for a variety of applications such as cyber-security and bioinformatics.
  • Selective descriptive pattern mining
    • How can we improve, in practice, the performance of different assocation, contrast, sequence, and action rule mining by incorporating user queries.
  • Action Rule Mining
    • How can determine, automatically, what factors should be changed that will shift convert an event/situation/object from an undesirable state to a desirable state?
    • Moreover, given the number of approaches existing, can we begin to provide som basis for determining the appropriatness of different approaches?
Return: Main page