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Overview

My Current Research Agenda in Geospatial AI

April 1, 2026
1 min read

I am currently pursuing an Integrated MS at IISER Thiruvananthapuram, and this post summarizes the research agenda that guides my present work.

Core Questions I Am Working On

  1. How can physics-informed graph models improve reliability in geospatial risk prediction?
  2. How can remote sensing and ground-sensor streams be integrated for operational decision support?
  3. How can we design data products that remain scientifically rigorous while being deployable in public systems?

Ongoing Research Themes

Physics-Informed Graph Learning for Fire-Risk Analysis

I have been developing PI-GNN based workflows to model spatio-temporal wildfire spread in high-risk regions of Kerala. My objective is to bridge physical priors and data-driven inference so that predictions remain interpretable under changing field conditions.

Time-Series Forecasting for Monsoon Onset

Using observational datasets, I have worked on improving monsoon onset prediction for Central India through structured time-series modeling. This line of work focuses on practical forecast accuracy and uncertainty-aware interpretation.

Synthetic Terrain and Geospatial Simulation

I have also explored reproducible terrain generation methods for geospatial analytics and simulation. This helps stress-test models in controlled yet realistic settings before field deployment.

Research Orientation

I approach research as an interdisciplinary exercise involving machine learning, domain knowledge, and implementation constraints. My long-term focus is to build systems that are technically strong and societally useful.

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