I completed my Ph.D. from University of Minnesota in the field of Spatial Data Mining (e.g., Linear hotspots, Taxonomy-aware
colocations, etc.), Statistics (e.g., Effect of spatial partitioning on the measures of inequality.), and Machine Learning
(Spatial variability aware neural networks). I am interested in discovering important and actionable information and gain
insights about the underlying processes and systems that created the data. I also explore ways to build smart automated
systems that work on interdisciplinary problems.
Brief Background: I have devoted majority of my college education and industry time to examine data such as, analyzing
spatio-temporal traffic movement, summarizing sentiment rich text, modeling real-time industrial sensors and classifying
URLs at network layer. My experience in industry has proved beneficial to bridge the gap between my academic knowledge
and industrial requirements. Further, my involvement in data exploration has made me eager to learn new techniques to
discover relevant and actionable information from large scale data-sets. Previously, I have completed my Bachelors and
Masters in Computer Science and Engineering from International Institute of Information Technology - Hyderabad (IIIT - H)
in 2014, Masters in Computer Science and Systems from University of Washington (UW) in 2015 and worked in industrial lab
at Bosch Research.