I am a graduate student in the department of Computer Science at University of Massachusetts Amherst. I am primarily interested in Deep Learning and its application to Computer Vision and Natural Language Processing.
Before coming here, I worked for a year at Samsung Research Institute, Bangalore in their S-Voice(Now Bixby) NLU Research division. My work revolved around intent recognition and entity extraction using deep learning technologies. Prior to that, I did my undergraduation from Indian Institute of Technology Kanpur with a major in Mathematics and Scientific Computing.
Explored the possibility of transferring information from high resource languages such as English to improve the performance of POS-Taggers for languages with low resources, in our case, Hindi in a completely semi-supervised way.
Used the tags obtained in this fashion in multiple auxiliary tasks and obtained significant improvement in accuracies.
Studied different methods of performing Zero Shot Learning(ZSL) - prediction of a label that
has been not seen during the training procedure.
Implemented two contemporary papers from this area which required learning a common semantic
space for embedding images and labels, to perform ZSL task. Focused on dictionary learning as a way to resolve the PDS issue and found that CNN based features drastically improve the classification accuracy.
Developed a framework to detect amplitude anomalies and shape anomalies within a temporal data over a time series.
An autocorrelation representation of the time series was employed to capture the shape information
m.Paani is a Hult-Prize winning social startup working on loyalty programmes for people living at
the bottom of the pyramid. Built an interactive map, for spatial data analytics, using web technologies and open
Presented the above tool to a CEO of a large company that is an m.Paani partner. Designed the front-end interfaces of m.Paani's loyalty management application.