I leverage data and artificial intelligence (AI) tools for positive human and climate impact. In the past, I engineered software pipelines to automate searches of terabytes of astronomy data for exotic events, including plausible signs of intelligent life beyond the Earth.
Major project highlights:
- Implemented a segmentation model to detect Amazon rainforest cover in satellite imagery with a 97% true positive rate.
- Conducted a rooftop solar feasibility study using LiDAR, revealing that 53% of homeowners in DeLand, Florida, can save over $1,000 annually by transitioning to solar-powered households.
- Developed a scalable tool for near real-time forecast of earthquakes induced from underground carbon storage, thereby enabling proactive measures to minimize the seismic hazard.
Outside of work, I enjoy following cricket, playing board games, and exploring natural wonders. Visit my personal website to learn more about my experiences in and beyond the workplace.
| Repository | Project focus | Technologies |
|---|---|---|
| agriyield_viz | Geospatial Data Visualization in the Cloud |    |
| amazonforest_segmentation | Test-driven Computer Vision Model Development |    |
| blipss | Software Development for Astronomy |     |
| may22-barrel | AI for Agriculture |  |
| oil-well-detection | Computer Vision for Satellite Imagery | |