ML@GT - CODA S1125H
Atlanta, GA 30308
I am currently a machine learning Ph.D. student at Georgia Tech. My research is in the intersection of deep learning and symbolic reasoning to enable label efficient and interpretable learning. The problem domains I work are across vision, text, and time series domains. I am advised by Prof. Irfan Essa and also work closely with Prof. Le Song and Prof. Mayur Naik. My other interests include feature engineering over graphs, interpretable ML, and healthcare ML problems.
During my summers I am fortunate to have internship opportunties so far at Amazon and at IBM Research. I previously worked at Astound as a Data Scientist, where researched and developed human-in-the-loop learning systems.
|May 17, 2021||Joined Amazon as an applied scientist intern within the Product Graph Team.|
|Feb 8, 2021||Presented my research to Prof. Irfan Essa’s group at Georgia Tech.|
|Jul 2, 2020||Presented an overview of visual reasoning on VQA and video tasks to the machine learning reading group.|
|Jun 15, 2020||Joined IBM Research as a summer research intern, hosted by Dr. Shankar Subramanian.|
|Aug 19, 2019||Joined Georgia Tech as a Machine Learning Ph.D. student. I was also awarded a Georgia Tech President’s Fellowship.|
|Apr 29, 2019||I recieved an Honorable Mention for my NSF GRFP Proposal: Relational Recursive Models for Trustable Medical Diagnoses.|
|Aug 13, 2018||I recieved a KDD’18 Startup Research Award , congratulations to the other winners!|
|Jun 6, 2018||Our paper Active Deep Learning to Tune Down the Noise in Labels was accepted at KDD’18.|
|May 12, 2017||Graduated from Purdue University with highest distinction. I will start working at Astound.ai as a Data Scientist.|