My primary research interest is machine learning.
I build machine learning, computer vision, and general statistical learning algorithms (and the corresponding computational systems) with applications in brain sciences, human in the loop systems, and more generally perception and cognition driven applications of artificial intelligence.
The crux of my research entails developing novel algorithmic techniques and methodologies by bridging domain-specific knowledge into the framework of machine learning and computer vision models. I do not work in theoretical aspects of machine learning. The list of such application domains that I actively work in are as follows:
Audio-Visual Learning & Perception for Augmented/Virtual Reality
Egocentric (First Person) Human in the Loop systems
Interpretable and Personalizable Learning systems
Some Useful Links capturing my group's research works
My group has also been vital in helping build large scale open source-able datasets for egocentric machine perception research. Check out the following two datasets and benchmarks we have designed over the past few years.
Prior to moving into Meta Reality Labs, I was working primarily in the following two application domains.
Brain imaging and Clinical Trials design
Multi-modal Predictive Modeling of Alzheimer's disease
Here is a copy of my CV (updated as of October 2020).