My project trajectory has been shaped by a single principle: applied AI should improve real systems in measurable ways.
Early Applied Systems Work
In the Young Innovators Program, I worked on Agro-Evolution for Precision Farming and Allied Sectors. As software development lead, I helped build AI-assisted nutrient delivery workflows for cultivar infrastructure.
The project outcomes were practical and measurable:
- Around 60% reduction in labor demand under software-assisted workflows.
- Around 15% lower production cost compared with manual delivery methods.
- Improved quality-of-produce indicators through optimized delivery planning.
Engineering for Public-Sector Use Cases
In subsequent roles, I worked as a project engineer and geospatial analyst on state-linked initiatives. My work included GIS product engineering for first responders and model development using remote sensing and on-site sensor streams.
I also contributed as a project manager and business/IP manager, where I coordinated timelines, budget reporting, and technology protection workflows.
Responsible AI and Professional Development
To strengthen my cloud and AI deployment practice, I completed the Google Cloud Skills Boost track covering:
- Large Language Models and Generative AI
- Responsible AI fundamentals
- Data transformation and modernization workflows
- Security and operations on cloud platforms
Current Direction
I am now focused on rigorous, interdisciplinary research that combines machine learning, geospatial science, and sustainability goals. I am especially interested in work where technical depth and public impact can be pursued together.