Developed an innovative edge matching methodology to effectively merge Land Use and Land Cover (LULC) layers from different states, and a methodology for merging districts within a state.Utilized popular libraries such as scikit-learn, Geopandas, RasterIO, GDAL, Pandas, NumPy, and Matplotlib to develop Python programs for supervised classification of raster data. These programs successfully performed tasks including LULC classification and extraction of water bodies.Led the development of a GIS-based web portal for Land/Water Resource Planning in India. Leveraged ReactJS with OpenLayers and Bootstrap for the frontend, Django with Geopandas for the backend, and PostgreSQL with PostGIS for the database management system.Created a web portal to display ground truth data collected through an existing Android app. Implemented ReactJS with OpenLayers and Bootstrap for the frontend, Core PHP for the backend, and PostgreSQL with PostGIS for the database management system.

Played a pivotal role as CEO in securing funding of 6 Cr. from GITA under the I4F scheme for the development and implementation of an AI-based earthquake early warning system in India.Spearheaded efforts to secure funding from NIDHI PRAYAS to develop a prototype related to the earthquake early warning system. Actively participated in the finalization of the prototype, ensuring its feasibility and effectiveness.Led the initiative to screen and secure funding from iDEX for the development of a tunnel detection system specifically designed for the Indian Army.Served as the industrial partner of IIT Roorkee for the project "Development of Low-cost Indigenous Earthquake Early Warning System" granted by the Department of Science & Technology, Govt. Of India. Successfully completed the project within the designated period.

Conducted research on the best practices for disseminating earthquake alerts to the public and identified the most suitable option for the Indian scenario. Developed dedicated public and home sirens, along with a dedicated warning dissemination system, based on the identified approach.Addressed the excessive cost and repair expenses of importing ground motion sensors for earthquake early warning systems. Designed and developed three prototypes of ground motion sensors using a modular design, ensuring compatibility with existing systems and enabling future upgrades as needed.Successfully tested the EEW public siren, developed indigenously for the earthquake early warning system, over two years in IIT Roorkee hostels. Utilized Raspberry Pi as a controlling board for the siren. Implemented encryption of warning messages to safeguard the dissemination system against hacking. Ensured small-sized warning messages to minimize network load and avoid congestion. (Framework: CodeIgniter with Open Layers, Bootstrap, jQuery, WMS Layers: Google Maps, DBMS: MySQL, Server: NGINX, Google Cloud, MQTT, SocketIO)

Led a team of six individuals and provided comprehensive training on the installation and maintenance of earthquake early warning sensors and sirens. Successfully managed the installation and maintenance of sirens and sensors for three years.Analyzed common failure reasons and implemented necessary software and hardware changes to rectify issues, ensuring the optimal performance of the EEW system.I actively represented the EEW system in various conferences, contributing to public awareness and education initiatives regarding earthquake early warning systems in Uttarakhand.Organized and participated in mock drills for the public, effectively simulating emergency scenarios and fostering preparedness among community members.Developed India's first mobile application for earthquake early warnings during this tenure. The app was officially launched by the Chief Minister of Uttarakhand, a significant milestone in enhancing earthquake preparedness and response capabilities.