Cooperative Institute for Research in Environmental Sciences - Earth Lab

Graduate Research Assistant
_{January 2024 - Present}

• Quantifying Aboveground Biomass Density (AGBD) for both pre/post-forest fires across the North Central region

Commvault

Software Engineer
_{January 2022 - August 2023}

• Elevated success rate for Commvault Cloud’s Remote Troubleshooting from 85% to 98%. Tailored a Commvault Report to monitor error rates, expediting prioritization of bugs and defects linked to Remote Troubleshooting
• Migrated and refactored a legacy codebase exceeding 35,000 lines for Remote Troubleshooting, upgrading it from Python 2.7 to Python 3.9. Introduced dependency management, log scrubbing, generic retry APIs, and incorporated keys to streamline code adaptability for both production and test environments
• Managed and updated the Commvault Plugin for ServiceNow to align with ServiceNow Store regulation
• Subject matter expert for Commvault integration with ServiceNow

Associate Software Engineer
_{July 2021 - December 2021}

• Single-handedly designed and developed “Decompress-as-a-Service” within the Commvault Cloud ecosystem. Orchestrated aggregation, decompression and notification functionalities. The service empowers 1000+ Commvault engineers to efficiently extract and process over 30 terabytes of Customer Logs everyday
• Implemented on-the-fly Maintenance Release Upgrades for Remote Troubleshooting, resulting in annual time savings of approximately 300 hours for the Cloud-Services Team
• Managed reports and workflows for Commvault Cloud

Intern
_{January 2021 - June 2021}

• Streamlined dependency management for the Cloud-Services project by migrating from Apache Ant to Gradle, resulting in reduction of build time from 3 minutes to 30 seconds
• Designed and automated test cases to ensure robustness of Commvault Cloud Disaster Recovery solution

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National Remote Sensing Centre - Indian Space Research Organisation (NRSC-ISRO)

Project Intern
_{October 2019 - April 2020}

• Conducted research on pre-existing work done to estimate coconut farm area from multispectral data
• Developed a novel deep learning model, Siamese U-Net, that addresses the challenge of estimating coconut farm area from multi-spectral data. Delivered a presentation on the findings at IEEE IGARSS - 2021
• The work resulted in a paper published at IEEE IGARSS – 2021

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Center for Data Sciences and Applied Machine Learning (CDSAML), PES University

Research Intern
_{June 2019 - July 2019}

• Conducted research on replacing clouds present in raw Sentinel-2 imagery
• Successfully designed and implemented a deep learning framework to remove clouds from Sentinel-2 imagery without training data under the assumptions of Deep Image Prior algorithm
• The work resulted in a paper published at Springer ICICC – 2021

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