As of August 2020, I am a member of Dr. Peter Song’s research group where my research focuses on information geometry-based causal discovery and inference. I have recently started exploring conformal predictions as well.
I’m also a part of the NIH-funded multi-centre Diabetes Foot Consortium of clinicians and analysts where we study diabetic foot ulcers, a common complication of diabetes and the leading cause of lower limb amputations in the United States. Led by Dr. Cathie Spino, my work involves the statistical analyses of ulcer-related wound images.
Since March 2020, I have also been working on studying and modeling the spread of infectious diseases with a group of statisticians, epidemiologists and economists led by Dr. Bhramar Mukherjee.
The Diabetes Foot
Consortium is a multi-centre consortium funded by the NIH. In
addition to performing standard statistical data analyses for the
consortium, I have built a web-based dashboard that allows clinicians to
access and download graphical and summary statistics associated with the
study. In this dashboard, I was able to automate some data pooling and
analysis pipelines, allowing for faster sharing of findings within the
group.
One of my earliest collaborations was with a group of
researchers from India who study trends in fish harvesting and its
impact on aquatic life in the eastern part of India. I wrote software
for implementing a Bayesian time series model that was successful in
detecting change points in fish catch data in Eastern India. Since a lot
of coastal communities in India rely heavily on fishing as the primary
source of income, being able to predict fish catch is critical for
advising policymakers on labour allocation as well as providing
additional support during times of reduced fish catch. This is, in turn,
helpful for improving the lives of coastal communities in India.
My collaborators have helped me not only with analyzing oceanography data but also with understanding the massive impact of climate change on countless fishing villages along the coast of India. I have continued with this collaboration and am actively involved with a new machine learning-based project for time series forecasting of fish catch data.
For more information on this project and related papers please see my publications page.
Ever since COVID-19 became part of our lives, I have been
involved with a group of researchers from the University of Michigan,
Johns Hopkins University, Harvard University, Imperial College London,
and other institutions from India, the UK, and the US to study and model
infectious diseases. Specifically, I have been interested in the
spatio-temporal forecasting of infectious diseases.
Among many other challenges in improving health disparities, COVID-19 was a stark reminder of how underprepared humanity is, in terms of informing and protecting those with an elevated risk of illnesses during a pandemic. I hope that through collaborative research, we have an improved understanding of how diseases spread and have differential impacts on many communities.
For more information on this project and related papers please see my publications page.