A little about me-
I am a first year PhD student at NYU's Center for Data Science, advised by Prof. Yann LeCun and Prof. Kyunghyun Cho.
Previously, I worked as a Machine Learning Engineer as part of the Data Science team of the Machine Learning Research Group at Oracle Labs in Burlington, MA.
I completed my Masters at the University of Massachusetts Amherst where I worked in the Information Extraction and Synthesis Laboratory with Prof. Andrew McCallum. My area of focus is mainly Machine Learning and its applications, primarily in the field of Natural Language Processing.
When I am not busy doing coursework or research, I love to paint and when time permits, keep my hobby of playing basketball alive.
Here's a list of my publications-Training Structured Prediction Energy Networks with Indirect Supervision
Amirmohammad Rooshenas, Aishwarya Kamath, and Andrew McCallum, NAACL-HLT 2018.
A Survey on Semantic Parsing
Aishwarya Kamath and Rajarshi Das, AKBC 2019.
Specializing Distributional Vectors of All Words for Lexical Entailment
Aishwarya Kamath* , Jonas Pfeiffer* , Edoardo M. Ponti, Goran Glavaš, Ivan Vulic, Representation Learning for NLP Workshop at ACL 2019.
What do Deep Networks Like to Read?
Jonas Pfeiffer* , Aishwarya Kamath* , Sebastian Ruder. Arxiv preprint, September 2019.