• As a scientist and an engineer, I am fascinated with information: what it is, how it is stored, how it is accessed, and how it leads to decisions. My doctoral research focused on how patterns in disk accesses allow a system to predict what data is commonly accessed together along with how this knowledge of momentary grouping can be used to make systems more available and power efficient.

    At Emory, my lab is exploring the dual of the storage problem. Whereas computer scientists have defined how to arrange storage to meet specific metrics such as fault tolerance and access speed, in neuroscience the metrics are observable but the system unknown. We are working to model information in the brain as a storage problem to better learn how we collect and interpret signals from our world, working towards a robust fault tolerance model for the brain. Other research interests in our lab include machine learning applications in neurobiology (particularly deep networks and topological data mining), archival storage, power management, privacy, and spatiotemporal modeling of storage workloads.

    My Erdős number is 3.

    Press:
    Interdisciplinary Work at Emory
    A bit about my work at Salk

    [Research Wordcloud]

    This word cloud represents popular words in my published papers. More details about my work are on my Research Page.