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\section{Research Direction}  We My collaborators and I  are using this observing mode in the first efforts to detect and image a new class of radio transient called "fast radio bursts" (FRBs; Thornton et al. 2013, Science, 341, 53). FRBs are believed to be cataclysmic events that originate half way across from far outside our Galaxy. If so, FRBs will be exquisite probes of the tenuous gas believed to reside in  the universe. Their fringes of galaxies (McQuinn 2014, ApJ, 780, L33) and may help in the search for gravitational waves (Zhang 2014, ApJ, 780, L21). However, their  great distance has only been inferred; no direct distance measurement exists, since FRBs have only been dtected detected  with telescopes with a poor ability to localize sources. Our commissioning of work has made  the VLA and into  the algorithms for millisecond transient detection has positioned us ideal platform  to make find and localize FRBs. We are in  the first precise localization midst  of FRBs. a 150 TB survey designed to find a sample of FRBs to determine what causes them and whether they can be used as cosmic probes.  The challenge posed by this 1 TB hour$^{-1}$ observing mode and 150 TB project are increasingly common in the sciences. In our case, the  internet is too slow to transport the 1 TB hour$^{-1}$ data stream, our data,  so we ship disks toour  computing centers. centers running our transient detection code.  This approach is too  complexand not sustainable in the large campaigns needed  to be applied more broadly. However, if we could support continuous surveys for millisecond transients, we could  find many fast radio transients. hundreds of transients for novel statistical tests of their origin and the composition of the interstellar and intergalactic media.  I am interested in developing Therefore, a long-term interest of mine is to develop  the concept of \emph{real-time anomaly detection} for massive data streams from radio interferometers.Real-time anomaly detection allows dynamic, data-based decisions that can change the way we collect data.  In the study of radio transients, real-time detection allows us to throttle the data stream to only the brief moments of interest. This process of \emph{data triage} is common in the particle physics community, where they have long been capable of building instruments that produce a deluge of data. However, in astronomy and other fields, scientists still treat every byte of data as precious, driving huge archiving costs and limiting our access to high data rate applications. Data triage  will be a key strategy to extracting science in data-intensive searches for "a needle in the haystack". %The technical requirements for our radio transient searchs are extreme in astronomy, but are becoming more common (e.g., see plans for %More broadly, real-time anomaly detection allows dynamic, data-based decisions that can change  the SKA and LSST). Lessons learned from our project will have increasing relevance to scientists working to solve the "needle in a haystack" problem. way we collect data.  %I am interested in thinking about how real-time detection can help solve the challenges of big data. By bringing computational support closer to the telescope, real-time detection makes it possible to decide whether a given segment of data is worth saving or not. This "data triage" may cheapen data, but it is necessary to access science in some high data rate streams.