About me

I am a Senior Data Scientist focusing on research in computer vision, remote sensing, statistical modeling, and high-resolution microscopy, to build optimized and automated end-to-end geoscience solutions.

Previously I worked as a Postdoctoral Researcher with the Center for Remote Sensing and Integrated Systems (CReSIS) at The University of Kansas, where I was the lead author on the seminal study that introduced Segment Anything Model (SAM) to the field of glaciology (Shankar et al., 2024). I focused on combining remote sensing with machine learning and deep learning models, towards climate change studies. My Ph.D. and Postdoctoral research dived into climate change by deep learning based iceberg detection and segmentation, and determining distribution laws that they follow around the Greenland Ice Sheet. This methodology used remote sensing imagery (optical & synthetic aperture radar), computer vision, machine learning, and deep learning. I created and managed large scale remote sensing datasets, with a focus on using open-source technologies and automation.

Along with my work, I also enjoy painting (mainly abstract expressionism, analytical cubism, and impressionism), and photography.