Generalisation in machine learning often relies on the ability to encode structures present in
data into an inductive bias of the model class. To understand the power of quantum machine …

Neural networks and traditional compression techniques can reproduce inputs with high
accuracy. However, downstream quantities derived from the reproduced inputs might be …

In scientific data compression, it is crucial to preserve Quantities of Interest (QoI) derived
from the data for accurate post-analysis of scientific applications. In this work, we present …

One initial step towards my research goal is efficiently and effectively processing sensory
data and abstracting them with symbolic or numerical descriptions, thereby generalizing …

My primary research interests are computer vision and deep learning. With the advent of
cheaper and smarter sensors, we have seen concomitant skyrocketing interest but have yet …