A Civil Engineering graduate from Nirma University with a CGPA of 8.78/10, has developed strong interests in sustainable infrastructure, environmental engineering, hydrology, geoinformatics, and climate action. They have served as a peer reviewer for Environmental Earth Sciences (Springer), reviewing research related to hydrology, watershed management, geoinformatics, Earth observation, and remote sensing. They hold professional certifications in LEED, SITES, building commissioning, clean air regulations, and ESG and net-zero practices from organizations including the U.S. Green Building Council, U.S. EPA, USDOT, AASHTO, Bloomberg, and UNU. Their leadership experience includes representing Gujarat at the Viksit Bharat Young Leaders' Dialogue and serving as an Indian delegate to the Harvard College Project for Asian and International Relations, as well as an Indian Ambassador at the Global Goals Summit in Kuala Lumpur.They were also selected as a participant and grant recipient of the Innovate4Environment programme, a British Council-TERI climate initiative, and received the 5th Best Speaker award at the SDGs Innovation Speak UP Competition at the Global Goals Summit Malaysia 2025.

SMARTSEA: An AI-Enabled Maritime Carbon Intelligence Platform for Scope 3 Emissions Monitoring and Sustainable Decision Support AbstractGlobal shipping transports approximately 80 - 90% of world trade by volume and is a significant contributor to greenhouse gas emissions. While much attention has been given to reducing direct emissions from ships (Scope 1), emissions generated across the wider maritime supply chain - including ports, cargo handling, warehousing, trucking, rail connectivity, idle time, empty container movements, inefficient routing, and supplier operations (Scope 3) - remain difficult tomeasure and manage. Many companies lack an integrated data-driven framework to identify where these indirect emissions originate and which interventions provide the greatest environmental benefit. As a result, inefficiencies persist, increasing carbon emissions, operational costs, fuel consumption, congestion, and delays. The project proposes to develop a Data Analytics-Based Maritime Carbon Intelligence Framework that integrates multiple environmental and operational datasets to identify Scope 3 emission hotspots, visualize carbon footprints, and recommend practical strategies for emission reduction