I am a first year computer science graduate student at UMass Amherst. My research consists of two major tracks. I work with Prof. Hong Yu on healthcare applications of machine learning. I also work with Prof. Yuriy Brun and Prof. Arjun Guha on projects in the intersection of software engineering and programming languages.
My current project with Prof. Hong is on reliable and interpretable prediction of critical patient events like mortality, bleeding, and heart failure, using electronic health records. Our most recent submission from this work was in the BOOM workshop at IJCAI-ECAI 2018.
With Prof. Yuriy and Prof. Arjun, I am working on a code completion tool for the formal verification language - Coq.
B.Tech in Computer Science and Engineering, 2014
Indian Institute of Technology Madras
Predicting clinical outcomes using longitudinal electronic health record (EHRs) data is a clinically important and computationally challenging task. In this project, we are working on predicting adverse events like patient death, bleeding, or heart failure using carefully extracted features from patient records.
Formal verification is an important field in Software Engineering and in Computer Science in general. With increasingly complex algorithms and models being implemented in today’s world, verifying their correctness has become that much more important. Formal languages like Coq help us achieve this task by providing us a framework to write proofs. However, the learning curve for these kinds of functional languages is steep since it involves rigorous proofs and the languages have a unique syntax structure. Programmers can use helpful suggestions about what tactics to use while writing their proofs. The aim of this project is to provide these useful suggestions by looking at previous proofs.
Teaching Assistant, Artifical Intelligence COMPSCI-383 with Prof. Phil Thomas, Spring 2018