Sangmi Pallickara Research
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Research Overview

Over the past several years there has been an exponential growth in the data generated by networked sources and observational equipment. These trends are visible in sensor networks, networked instrumentation, and remote sensing using radars and satellites. My research focus is on Big Data, specifically scalable knowledge extraction and storage systems. My research targets: (1) Effectively storing voluminous, rapidly evolving datasets that encompass billions of files with trillions of observations. This involves addressing algorithmic and system issues to disperse loads, effective state synchronization, and Instrumentation and evaluation of a rich set of expressive queries. (2) Facilitating construction of deep learning models over geospatial observations at scale. (3) Enabling storage and analytics when the pace of data arrivals exceeds capacities. (4) Supporting interactive visualizations over voluminous datasets.



Curriculum Vitae [Download]

Publications [Link]